There is seemingly a bug in the treatment of WHERE dataset option in the SCORE statement of PROC LOGISTIC SAS 9. Consider the simple test:. This question is not related to the subject of the discussion, it should have been submitted as a new discussion. But the answer is GOOD. Convergence means that the procedure found parameter values that maximize the log-likelihood, i. I am using PROC LOGISTIC to build a multinomial logistic model using dataset A and then score the second dataset B. Both datasets have weights, and I would like the model to be built based on weighted data in A and then applied to the weighted data in B. However, it seems like PROC LOGISTIC allows for weighting only the first dataset, but not both. If so, what would be the best way to solve the problem? In Proc Logistic we can add 'Units" statement to change the unit of the explanatory variable. Is there any equivalent statement in Proc Genmod procedure? I need an output showing " unit change of independent variable" rather than the standard "one unit change Hi can any one help clarify doubt in goodness of fit in binary logistic. I created a model to predict the event response and got excellent c score of about. Also the KS score looks significant. Only thing I am having a trouble with is HL Hosmer Lemshow statistic coming significant means I need to rethink about the model. My question here is can i ignore the HL test and rely more on predictive power? Also, I am using proc logistic here. Appreciate any help on this. The Hosmer-Lemeshow test is not my favorite test; it has low power in smaller samples and can show significance for important deviations in vary large ones. I much prefer to look at the observed-predicted plots themselves. If the HL test is significant, it doesn't say that the model you have is "wrong," it options that it can kkd "improved. However, if the model seems adequate, I may just "declare victory" and move on. One caution that doesn't seem to matter hereif the HL test is significant, then it would be inappropriate to claim that nothing is going on e. I want to compare the survival curve for a treatment and a control group. For that i have done propensity scoring and then did matching based on the scoring. I would like to know how to incorporate matching in proc phreg or proc output to get survival curve. Again what are the test available in proc phreg and proc lifetest to check for the equality of the two curves treatment and control. Proc lifetest gives wilcoxon sign rank test. But does it gives sign test result as well. For some reason my code doesnt work. PGStats, since I am using Enterprise Guide 4. Is there some other way to do so? Can anyone provide me with the formula sas uses to calculate correlation coefficients using the corrb option in logistic regression procedure? I am trying to produce a correlation matrix among variables and I get diffrent results when using the proc corr. There is a bootstrap tool on the SAS support web site that works well. Check out this knowledgebase article:. I am in the process of sas the ins and outs of using PROC LOGISTIC to conduct stepwise logistic regression. One thing I noticed about in the help manual is that during the backwards elimination step of the stepwise procedure, it uses the Wald test to determine whether or not to remove an explanatory variable from the model. Is there a way to specify either the score test or the likelihood ratio test? I am asking because we know from Hauck and Donner JASA that the Wald test displays unusual behavior when applied to logistic regression. I would like to calculate odds ratio to compare the odds for treatment A and B, treatment A and C, treatment B and C. But what I obtain is the odds ratio for only two comparison. I notice that the odds ratio and the confidence interval are the same in the two cases, but the p-value is different. Can someone give me the position of the Slice Statement in Proc Logistic syntax? I've put it all over the place and I keep getting the above error about invalidity or sas order. Unless you are operating on a version earlier than 9. I'm new to SAS and I am currently processing a large number of plots using the proc logistic procedure. I need a way to automatically update the plot title and axis labels as each plot is produced. I have spent a few hours wading through the manual and cannot find an explanation how to do this. Can anyone steer me in the right direction? I want to use 'sampling weight' but my data sets don't have 'strata' and 'cluster' variabels. In my situation, what should I do? Or can I use 'proc surveylogistic' procedure with weight variable but without strata and or cluster variables? Second, in 'proc logistic' procedure, what does 'weight' statement mean? Does 'weight' mean 'frequency weight'? Sampling weights are used to calibrate parameter estimates calculated based on a sample. Just check proportion of 1's and 0's in your population data and compare them with sample proportions. This will provide a baseline to create weight variable that can be used in proc logistic. I'm doing some logistic regression analysis in EG 4. I know the EG method just generates a PROC LOGISTIC call, but from a quick look at the help files it seems that there are a few options that aren't incorporated into the GUI. Is there a concise list of which options are only available if I write the code myself? Of course, I forgot about the code hooks. Of course, regression still requires you to know or be able to learn all the bits of PROC LOGISTIC anyway, but that's not necessarily a bad thing after all, it's good practice to know how your code is doing what it's doing, instead of just blindly hoping that it will do it right. I have seen on some outputs alledgedly some nice tables with the observed responses on the left and the predicted responses on the right. In each cell, there is the frequency of people taking the corresponding observed and predicted responses. For the moment, I use the "Association of Predicted Probabilities and Observed Response" with the "Percent Concordant" thing. What you are looking to is called "classification table". You should try the CTABLE option in the MODEL statement options ; this is not really cross-tabulated, but contains all information you need. You can also create predicted observations with the OUTPUT statement, then create a format with PROC FORMAT to transform continuous predicted probabilities into binary predictions e. I am working with Proc Logistic and I am using the Stepwise process. SAS gives a detailed output, among which there is a table titled "Analysis of Maximum Likelihood Estimates" which contains all the variables present in the final model as well as the intercept term in the rows and the estimated coefficients, DF, p-values etc. How can I quickly output this information to a SAS dataset? Can anyone tell me which options to invoke in the proc logistic statement or the model statement or anywhere else? Check the log for the output that you want turned into a dataset. It will typically be listed under a path, i. I fitted an ordered logistic model using Proc Logistic, and now want to feed in a new set of independent variables values to the model coefficients. In the end, I want to see new outcome variable values with confidence bands around them for the independent variables that I fed in. Can anyone help me with the sas code for robust logistic regression model? When I looked online, all information is about proc robustreg. But I cannot find much information about the robust logistic regression. Anyone has any sas about how to take care of the outlier in the logit and tobit regression models? In the output of PROC logistic, I can get the upper UCL and lower LCL confidence limits of the predicted probability. It seems to me that the standard error produced by this formula is way smaller than I would expect. The confidence limits for the predicted probabilities are computed as shown in kkd "Details: Linear Predictor, Predicted Probability, and Confidence Limits" section of the LOGISTIC documentation:. Anybody have any tricks to avoid the output from PROC LOGISTIC, especially in the "Analysis of Maximum Likelihood Estimates" section. And when one of the variables shows up in this section, I have no idea which one it was! It will trim them off at a certain length. I am using the PROC LOGISTIC to conduct exact logistic regression. There are two main exposures: Both are two-level factors. I am interested in the effects of A, B and their interaction on a binary response variable, adjusted by other covariates. So, regression logit is: Did I understand correctly? I'm trying to run a model using Proc Logistic but I get an error message saying "no valid observations". Can someone tell me any other reasons as to what might be causing this?? I am not sure if this is something that you have thought about but it may be possible that people with answers to one of your indicator variables may not have responses to another variable. This was the case in one of my examinations where people who responded to one question in my survey often skipped a question later on. This may look like what you have already said, but when a large number of variables are used as indicators, it is possible for each variable to have a high response rate yet output get the error message. One requirement for an observation to be included in the logistic regression is that it must have a complete response to ALL variables in the model. Take the below as an example. You might want to think about doing some investigation into imputation, where the responses you do know can help you impute the missing values and you can still utalize the variables in the model. So i'm using proc logistic and a little confused. I have some variables which are strictly categorical; however, i've used integers to denote individual categories for ease. Now i am pretty sure sas is seeing them as being ordinal, but i need proc logistic to not recognize them as such. The data in the variables is numeric. Is there some way i can get proc logistic to recognize these variables as such without converting all these values over to character values? Hi, I am trying to do multiple imputation. I've given it a shot for the entire day, but something is wrong. I run a macro below. It's just a simple cancer vs abx univariate logistic regression model. What does the warning indicate? I am using PROC MI first no errors and then PROC logistic, and then PROC mianalyze. What is the most painless way to do multiple imputation for categorical variables? I see this IVE software, but Sas took a look and that looks like another learning curve to learn how to use. I'd prefer to do it in SAS 9. I know options question was posted a few years ago, but I ran into the second problem listed here and thought I would post how I solved it in case anyone else runs into it. When results are sent to the parameter and covariance data sets, the parameter names in the parameter data set have a set length of 20 characters. Change the variable name to a shorter one and it solves the problem. For the first question, it seems that having between-imputation variance of zero would indicate that there were no differences between the results for the imputed data sets, and thus no differences between the imputed data sets for these variables. If both variables are dichotomous and you had a good number of predictor variables and few missing, this seems reasonable. I tried this with my own data, with two dichotomous variables with only 1 missing respondent per variable. The imputed values were the same in each imputation, and when I ran PROC LOGISTIC and then PROC MIANALYZE I got the same warnings you did. Could anyone please forward me code for generating a table with AIC and AICc values in Proc logistic in SAS 9. I was afraid of that. I will use the AIC values to compute AICC in Excel I ran some chi-square tests for a binary dependent variable and other binary independent variables. Now I'd like to build a model using all of the independent variables in proc logistic; however, I've been trying to run proc logistic on the dependent variable and one of the independent variables to see if the odds ratio corresponds to the odds ratio I got using the chi-square test. After reading about proc logistic and trying several different code iterations, I haven't been able to get the same odds ratio. Although I've been programming in SAS for years, my stats experience is limited and I feel like I'm missing something. Using your input, I ran my code with the event option '0' and changed the ref option in the class statement to '2' and it worked my independent variables are 1 for risk factor present and 2 for not present. I appreciate your help. I have found that PROC VARIOGRAM in SAS 9. I'm not familiar with all of the assumptions underlying the use of Moran's I. Does anyone know if it is appropriate to use Moran's I to test pearson or deviance residuals generated from PROC LOGISTIC for spatial autocorrelation in a output model vs OLS? I am building a logistic regression model using PROC LOGISTIC with a sample data. Does anyone know how to get around this issue with weight incorporation?? It is very clearly described in the documentation on the SAS web site; look at the MODEL statement section. I am currently doing a Logistic Regression course and was wondering if there was a way to get PROC GENMOD to calculate the odds ratio. Paul Allison's book suggests that there isn't but I wasn't sure if this has been updated in more recent version of SAS. There is a link in this note to a document showing examples of writing CONTRAST and ESTIMATE statements. Examples of computing odds ratios using these statements are given in that document. While an example using GENMOD is not specifically shown, the same method applies. You could easily change the example using the CONTRAST statement in LOGISTIC to use the ESTIMATE statement in GENMOD. The answers to many questions can be found in the Samples and SAS Notes in our searchable knowledgebase, http: You can use the search engine there to find the answers you need. I am trying to get white standard errors test in my logistic regression. I read a few articles on the internet and came up with the following code:. When I am running a proc logistic model, what syntax I need to add in order to let the MSE value appear at my output? Since PROC LOGISTIC uses maximum likelihood methods, there is not a real MSE generated at any point. The standardized deviance residuals and the likelihood residuals available in PROC LOGISTIC in SAS 9. So, values greater than 2 or less than -2 might be considered suspect. I want to use an instrumental variable in survival analysis, and I think the PROC SYSLIN is only for linear or logistic regression? Is there command specifically for Cox proportional hazards model? Well, there should be a Wald chi-square test in the output for PROC PHREG for this variable. However, some comparisons produce warnings in the SAS log that I want to get regression of properly. The warning I refer is:. There is possibly a quasi-complete separation of data points. The maximum likelihood estimate may not exist. I can't change the model or anything proc logistic. The requirement is to not perform logistic analysis for such data. Is there a way in SAS I could reliably check data if proc logistic will through this warning or not without producing errors or warnings in the log? NOWARN options is not a solution, because I need to see warnings for other cases and to skip data for logistic regression. I like the Firth penalized ML method, but if that is not available due to prior decisions, I would try something like:. I would then look at any situations where the sum was zero for one of the combinations of the independent variables. By including appropriate ID variables, you could then exclude these cases from the dataset. This assumes that the quasi-separability arises from categorical predictors which have only zeroes or ones, but it is easier to find the zeroes for some combination of the predictors. How can i perform the LR statistic test in the Logistic Procedure instead of Wald test? I now that i can perform it with the GenMod Proc. How does SAS calculate 'xbeta' output in proc logistic? I am using censored data and the Heckman Two-Step method to run a regression analysis, so here's the dilemma:. If so, then the above code is accurate. In PROC LOGISTIC, xbeta contains the estimates of the linear predictor. It is not scaled by sigma, I beleve you will have to divide through by the pooled output estimate to get what you need. I am trying to figure out how to create a logistic model that has no explanatory variables to act a my "null model. Can I do this using either PROC LOGISTIC or PROC GENMOD? I have included my coding below for: OK I actually figured it out. For anybody interested, it can be completed using PROC GENMOD. Similarlyi want to increase the length of "variable" column in parameter estimate table. Here in proc logistic by default it is taking 20 length,but my variable names are greater than I am wondering if I cant just exclude one group from my class variable by the logistic regression I mean, if I have the variable age:. If I see that for example the age2 is no significant, can I just delete this group from the logistic procedure? I am running Proc Reg to check multicollinearity for logistic regression models. Almost all the independent variables are categorical variables. I constructed dummy variables and put K-1 dummies in Proc Reg models. I am wondering if I use the same model for these two options as the later will exclude the intecept from calculation. Kkd more than one categorical variable, I would run the collinearity diagnostics using k-1 dummy variables for the i-th categorical variable AND I would include the intercept. By using k-1 dummy variables for the i-th categorical variable, you do not overparameterize the model with the reference level for any of your categorical variables. Inclusion of the intercept along with the k - 1 dummy variables also does not result in an overparameterized model. If you were to use k dummy variables for each categorical variable and you have two or more categorical variables, then you will end up with an overparameterized model. So, it is best to use k-1 dummy variables and include the intercept. I wanted to ask what SAS procedure would be adequate to make a conditional probability table. For example, a table that can display a probability for gender given age or something of that nature. I was reading up on the proc logistic procedure and proc freq procedure. However, I don't have a model to do proc logistic as of yet, the data is pretty raw and I wanted to have some quick descriptive statistics involving age for some variables. One more question for the community, if I do any modeling like in proc logistic, does my data need to be normally distributed? Hi Regression, Just a quick one regarding proc logistic in SAS, I have entered 15 variables in my model and 14 variables seem to be good, does it mean that I should keep all of them in my model? Also I have troubles at understanding the concordent and disconcordent. Does it mean that the model has predicted If I add variables or remove which statistic should tell me that the model is still good. Is it C AUC value? In the past, I was using another software to build models, so I am bit lost. This seems to be an overfitting problem, I suggest check collinearity before adding variables in the analysis. I tried a formula based on the Estimate column: Which info from the output I should be using and what is the transformation if any required? It is a one-way model with the fixed effects going over time. One of my independent variables is lagged two periods in the past. It is a count variable that is closely related to the dependent variable. My concern is that the variables are sufficiently related to cause some serial correlation in the model. I'm trying to get the dispersion statistic out of proc logistic. It works when I use output aggregate option but not when I don't. I know that genmod produces the deviance and pearson statistic but in SAS 9. Dispersion cannot be computed for individual data. You must define subpopulations and this is what the AGGREGATE option allows you to do. See this usage note on overdispersion: In the file attached you'll find an example of dataset I'm using. I have to run a proc logisitic "Responders" is the dependent variable taking into account the data repeated measures variable period. How can Sas get the Hosmer Lemesahaw Goodness of Fit test to work on scored data, i. I want to score new data using a previously fitted model and get this test. I also want to score a 'validation' data set for this year's data. To do this by guessing I ad a line of code:. This appears to give me the ROC plot and Fit Statistics for the data, but of course, I can't figure out how to get the Hosmer Lemeshaw test on the 'scored' developmental data. I can't find a way to add a 'LACKFIT' option anywhere as I did for the developmental data set in the MODEL statment. The purpose output my model is to assign probabilities to 'patrons' that use our service. I want to concentrate our efforts on those that the model predicts to be 'in the middle of the road. Most all individual predictors are significant at. Can you, or someone give me their opinion about how much importance I should attribute to the HL test with regards to the utility of my model? Most of the papers that I have reviewed options even report HL results. It remains an interesting question for research whether fitting y well or obtaining good parameter estimates is a preferable estimation criterion. Evidently, they need not be the same thing. Using output and manipulating with data: The problem is following. This may have been tacitly alluded to here, but I was thinking that SAS used a leave-one-out LOO method for calculating the SEN regression SPEC in the ctable option. I am analyzing case-control data collected from 4 different hospitals. I wish to know how could the parameters of control data be applied to case-control data. Is there any command like these in Proc genmod? Problem is, I have hundreds of variables in my dataset. Is there a way to not have to type them all out? After running a logistic regression i get the output containing the estimates for the scoring variables. My question is the following, how do i interpret the estimates of the continuous variables that i have used to someone? How can i show him the likelihood of an event based on that estimate? What does a 0. Here is link to SAS STAT user guide that has some details on how to interpret proc logistic. For more depth, check books written by Paul Allison. If you visit www. In categorical data analysis, SAS generates Somers' D to test the association strength between categorical variables. In SAS, both Proc Freq and Proc Logistic generate Somers' D. My question is what is the difference between the Somers' D from Proc Freq and Proc Logistic? Most of time, Somers' D from Proc Logistic when only one factor is applied is quite closed to the Somers' D from Proc Freq. However, they could also be quite different. Could someone tell me what make values from both Procedures so different? The method of calculation may differ quite markedly for each procedure to allow for the functionality provided by the analysis. The calculation method for each procedure is explored in great detail, and will make profound sense to someone who understands statistical techniques and the limitations of particular interpretive methods. In the documentation, the term Adjusted Odds Ratios is only used once in association with proc logistic. I have a question regarding the model statement syntax in proc logistic. I read that the below two model statements are equivalent. The bars separating the variables tell SAS to consider interaction between those variables, but the 1 says to only consider single level so no interaction. I'm using proc logistic and have several categorical variables. The data, though, is numeric, some with corresponding formats, others binary, etc. Is there an easy way to get proc logistic to recognize the variables as categorical? I tried to list them under class, but this didn't work of course since the data is numeric. Do i simply have to reformat the info? How do i do this in an efficient manner? I think i was forgetting to put my values in single quotes. Why is it not possible to construct receiver operating characteristic curves when implementing conditional logistic regression? From a SAS perspective, why is it that we cannot use the 'strata' statement and the 'outroc' option in proc logistic? ROC that you can request in PROC LOGISTIC is based on predicted probabilities, and we do not obtain predicted probabilities with conditional logistic regression. This forum gets a lot of questions on logistic regression. So I wanted to let people know that there is a new book from SAS Press that should be on the desk of anyone interested in this topic. My copy of Logistic Regression Using SAS; Theory and Applications, second edition, by Paul Allison, arrived a couple of weeks ago. It is a wonderful text. I think the book is equally valuable for novices and for experts in logistic data analysis. Paul fully incorporates all the new features in PROC LOGISTIC and in many other procedures. I am running several proc logistic models, utilizing the odds ratio estimates. Note the 1 vs -1 for the parametrization, rather than what you'd expect. Anyways, I think the issue is with the weights statement instead see last message. Try surveylogistic instead of proc logistic. I have not seriously investigated how the PPO model is fit using the GENMOD procedure. However, I do know that you have to employ an altered construction of the data and that PPO model estimation employing the GENMOD procedure then requires a GEE model to attempt to account for the covariance of response levels which arises from a multinomial distribution. But the GEE only approximates the covariance of the response levels. Moreover, the GEE which is employed to account for the covariance arising from a multinomial response requires specification of cow as the subject. But you wanted to use a GEE to account for correlations between cows due to clustering in herds. Thus, the PPO model fit employing the GENMOD procedure does not allow appropriate modeling of all of the correlations which appear in the expanded data. The NLMIXED procedure does not require an altered data construction AND it does fit the multinomial model. Covariances between response levels are accounted for in the likelihood maximization process. Moreover, you can incorporate random herd effects to account within-herd correlated responses. When you fit the PPO and PO models employing NLMIXED, you test the proportional odds assumption employing a likelihood ratio test rather than a score test. I have not studied score and likelihood ratio tests for testing the proportional odds assumption. However, my guess is that a likelihood ratio test would have better properties than the score test. I can't guarantee that you won't have problems fitting the PPO model employing the NLMIXED procedure. However, the NLMIXED procedure has much going for it over the GENMOD procedure for estimating a PPO model. I'd like know if SAS has an inbuilt command to do penalized likelihood estimation for a binary logistic regression taking into account the study design at the same time? Thus, Firth's method is inapplicable in this procedure. However, some have attempted to mimic this design-based analysis of complex sample surveys using model-based methods like generalized linear mixed models in PROC GLIMMIX. I ran a model using proc logisitic and proc surveylogistic and upon comparing the results I found the OR estimates to be same as one would expect however, the parameter estimates were different. Upon taking the EXP of the parameter estimates from the proc logistic output I was able to reproduce the ORs but I was not able to do the same with the parameter estimates from the proc survey logistic output. As a result, I believe the parameter estimates from proc kkd to be true. This creates parameter estimates that via effect coding not referential coding which is probably what you're after. Check the docs for further information. Also, if you're using weights you should be using surveylogistic, again check the docs for the reasons. I used PROC LOGISTIC to run a model using backward variable selection method. For this method, the final set of variables that were kept in the model have p-values 0. Can I ask how I can control the significance level for the final variables in PROC LOGISTIC? If you have interactions in the model, the default is to maintain a heirarchical model. In such a case, A or B may not meet the significance level requirements. I am facing an issue regarding the score statement after performing the proc logistic procedure. I do not understand how i will create the input for that, I have been browsing through the net but no clear answer, hoping for an answer here. You can do scoring and much more with the new PROC PLM procedure. I recently suggested it and had a consultant tell me it wasn't valid, but SAS produces it and I've read articles that suggest its a valid measure, though it doesn't have the same meaning as in linear regression. The current fashion with binay outcomes in the logistic model is to use the C statistic, based on ROC curves. Available in SAS and is interpretable in terms of PPVs. Rather than trying to explain away variation in the outcome variable, you are attempting to determine how well your model predicts that outcome, so to speak. I used "proc logistic" to model an ordinal variable. I have the problem, that I don't know, what is the criterion, to add or to drop variables. I found some ways in the literature. For example, that you can do it with the p-value of the likelihood-ratio-statistic. In SAS EM version In HP STAT product They are under stand-alone SELECTION statement. The whole HP STAT package does not require huge investment in hardware to run. It is available as upgrade to your regular STAT. Computation wise, all the HP procedures are designed to run on multi-threads. On this computer I am typing this reply, there are 4 cores and 8 threads in total. Generally, if all possible, one may want to engage hold-out data earlier in modeling estimation and selection. In HPREG, a separate PARTITION statement is already built in. Could anyone explain to me what is the difference between the above mentioned methods? Trying to build a model for churn and pondering over which one to choose to achieve better results. Logistic regresson in general deals with situations where you are trying to classify subjects into cases, often binary, but it may be ordinal low, medium, highor nominal choice of food, for example, there is no scale or ranking within these classes. SAS has a number of procedures that can handle logistic regression, Kkd LOGISTIC being one of them, and has been around a sas time. But it's not the only PROC that can handle logistic regression problems. PHREG - proportional hazard models deal with survival analysis where the TIME dimension is very prominent in the analysis. The interest is on the hazard function. The data structure is quite regression bit more complicated, especially if youhave time-varying covariates. For churn problems, sometimes for convenience, one picks a fixed timeframe, say 6 month or 1 year, then the question of how long will each account survive gets transformed into "within 6 month or 1 year, what is the attrition probability", a problem that logistic regression can handle. They are often related by the type of problem they are pressed to solve, but the underlying thinking, view of the problem, and mathematics are quite different. Like MIXED, default is reference coding, and GLIMMIX does not have an option for changing this reference coding. Thanks in advance for any help I may get. It seems very confusing to me and I have no idea about the reason. A intense Google search didn't find anything. The c statistic in the result is 0. Percent Concordant is The c statistic becomes 0. They all are very different from the previous set of values. The result proves that. I would like to suppress the subtitle "conditional analysis" in the ods output from conditional logistic regression models. Here is code snippet Thanks, I was able sas get rid of the unwanted subtitle when I replayed the OR graph output "proc document" by using the obstitle statement with no title specified. SO I am having trouble knowing why my predicted probabilities do not match up with what I expect it to. It kind of depends on what coding you used for the dependent variable. Do your predicted probabilities look like 1 - expected prob? Or are they completely mucked about? I wonder about this because of the 0 in your manual equation--I assume that it is a negative sign in your actual calculations. I'm currently experimenting with Bayesian methodology that SAS has made available in 9. In particular, I'm using PROC MCMC to generate a logistic model. However, unlike PROC LOGISTIC, the determination criteria for whether variables are significant is missing. From reading the documentation, it appears as if SAS only makes available the deviance information criterion DIC. Is this the only viable way SAS enables to determine variables that should be in the model? Really--it has less bias than other methods statistically, at least for variable selection. There have been some significant discussions both here and on the SAS-L listserv about variable selection. PROC GLMSELECT documentation under Model Selection Issues talks about many of the drawbacks. It also implements least angle regression LAR and LASSO methods. It has been shown that these methods can be extended to logistic regression. And of course, a lot depends on what the model is about--explanatory hypothesis testing or predictive ability. Get a copy of Frank Harrell's Regression Modeling Strategies for a good look at methodologies. In SAS Enterprise Guide, when I run PROC LOGISTIC It's immensely annoying because it causes clutter and it always readjusts the positioning of my objects. Any way to suppress this behavior? Hi,I am trying to conduct a lack of fit test on a logistic regression model in SQL As a result the linear regression work around does not seem to work as it does not work with discrete variables. Apart from migrating to SQL is there anyway to conduct a lack of fit test making use of the above proc? You task is actually related to Measuring or validating model accuracy. This is usually addressed by holding out a certain percentage of training data to validate the accuracy of each model. SQL Server added support for holding out and cross validation. Please refer to the following articles for more details: The Lack of Fit is something related to Sum of Square Errors, so it only apply to continuous output. Please refer to the following wiki page for details: I understand that one method is to perform stratified sampling. But I also read that Firth method is possible too? Logistic Regression for Rare Events Statistical Horizons. You might want to check out the paper by King and Zeng, "Logistic Regression in Rare Events Data" that addresses the rare events problem and also cites Firth's paper. I am interested in knowing how you have progressed with the modeling of the rare data, as I have a similar extremely rare events data to process. I'm running PROC LOGISTIC and some of my independent variables are dummy variables. Do I need to include these dummy variables in the CLASS statement? I've run it both ways, including them in the CLASS statement and excluding them, and while I get the same Pr ChiSq both ways, the estimate is different each way. In fact, when including the dummies in the CLASS statement, it appears that the estimate is in the wrong direction. What's the difference here? If so then you don't need to include it in the CLASS statement. The opposite sign on the parameter estimates may be due to the difference in the reference level. You can set your reference level explicitly in the CLASS statement. I have a proc logistic model with an interaction options between a binary variable and a continuous variable. How can I get SAS to give me or how can I easily calculate the p-value associated with these ORs? For details and an example, see this usage note:. I know it is possible to do that with proc logistic. But I need to have a random effect in the model. I have more than 50 independent variables to create the model. It will be nice to create this code as a help to create the final model. Read Walt Stroup's Generalized Linear Mixed Models to see how, especially in smaller datasets, marginal models are biased compared to conditional models. Naive fitting using pseudo-likelihood methods for distributions without a free scale parameter would be the most likely candidates. Hi, I was wondering if someone is able to answer a few questions that I have. Is it possible to put the logistic regression model in PROC REG? Thank you Jason and Paige for your input it has been VERY helpful. I am also confused about another topic and I was hoping one of you might hold the answer. I am trying to examine influential observation in some logistic regression models. However, I am not sure what cut off values I can use to identify inlfuential observations for the Deviance and Pearson residuals? If so can I just use the absolute value of 2 or 3 as in standardised residuals in linear regression. I am aware that you can generate plots of the residuals aswel but I was hoping there might be a cut off value that I could use aswel. Are these values used to detect the influential observations and how are they used? The scored data contains missing values due to a class level which is not in the training data set. In other words, I would like one specific variable to remain in the model, while all others are allowed to be excluded or included depending on their significance. Are you using JMP? JMP doesn't have "procs" per se; maybe you want the SAS PROCs forum: In the excel attached, For the 1st tab - 'Step 1" I have figured out the code via external assistanceto get the desired output but what I don't get is the way to run the logistic proc on the original data set to get the desired output as shown in the 2nd tab of the excel attached. The proc logistic will include only those independent variables which have a mean 0. Well, since I will be writing the code for 'proc log' for the first time, I may not be sure about the accuracy but I will try out Tom's suggestion and see how it works. My ultimate aim is to achieve a 'data set' through 'proc log' output as given below Is there anyone how know how we can set cutoff f. Also We want to set cutoff with cases less than score with 0. With any model you can set the cutoff to whatever you want at query time. I'm not sure what you mean by cutoff, but you can either filter them out or return to the calling process. I have a data-set that contains variables. When I used proc logisticproc logistic sparsed through these variables and showed 14 variables that were significant p0. Will neural network do the same? If I use neural network in Enterprise Minerwill it go through all the variables and tell me which variables are significant for a specificy dependent variable? I options trying to perform logistic regression with Lasso. For the logistic regression part I am using PROC LOGISTIC but I am not sure how to do Lasso with it. I searched online an and found that PROC GLMSELECT allows us to do lasso. But I am not sure how to options a Lasso on Logistic Regression. PROC GLMSELECT cannot perform logistic regression with LASSO. An example is as follows: This is an empirical question. Once you get that going, I think I have seen a rule of thumb of 10 responders per independent variable estimated in the model. Should be a good starting place. Is there a way to specify this in the ODDSRATIO statement? Not sure if the ref needs to be in quotes or not, but you can verify in the docs. May also be version issues as mentioned by statdave. Hello, I need to adjust my p-value for significant interaction term in the adjusted logistic regression model with quite a few covariates which i have to keep in the model. I have no clue how to do that. I tried PROC Multtest but then it is not logistic and does not allow to use for covariates, and then I have no possibility to input raw p-values so my raw and bonferroni appear the same! Is there any option in PROC LOGISTIC that would allow me to adjust for comparisons? Note that the first argument is an interaction term. Removing the interaction from the covariate list or switching the selection method to BACKWARD eliminates the problem. I usually spend a lot more time writing code with NLMIXED, so I can't just set something up and let it cook for a couple of hours. I have 90 data divided between four types of organism, lets say fruit. I've tested them all for something and decided they each have none of it, some of it or all of it, so I have three ordinal levels. I would like to run a logistic regression to see if the type of fruit is significantly associated with level of "something". So, I would normally run a logistic regression and Proc Logistic would use a cummulative logit function. Kkd problem I have is that I could only test six fruit at a time, so my data are stratified. When I add a Strata statement to the Proc Logistic model I receive this message in the log:. I could collapse the data into Binary except that isn't really satisfactory in this particular case, since having "some of it" is treatable and not terminal, so it's useful to know if "some of it" is associated or not. Could I take out the Strata statement and simply include a strata variable in my model? I'm wrestling with the underlying implications of that possibility - maybe I have been at this for too long because it is not immediately apparent to me if that would be legitimate or not. I suspect not, so I am peforming proc logistic with the exact option. I keep getting an error message that reads The model runs and get odds ratios and confidence intervals which are comparable to logistic without the exact option. I am just confused as to why I am getting this error and what it means. I only have people in my sample. That's what I have come to find out. But it was suggested that I use it anyway. The "accuracy was lost" warning means that in compiling the exact conditional distribution, some frequencies became extremely large. See "Exact Conditional Logistic Regression" in the PROC LOGISTIC documentation:. See also the comments toward the end of the "Computational Resources for Exact Conditional Logistic Regression":. As noted there, this message isn't necessarily problematic. It's just letting you know that the exact counts could not be maintained. Given the complexity of the exact algorithm, it's not really possible to track the cause of regression message back to some feature in the data or model, but this problem is increasingly likely as the data set size increases. For data sets which are too large options the exact method, the Monte Carlo method available in SAS 9. I got different results when running logistic regression using Proc Logistic with interaction term. One way, I directly put the cross product term in the model statement of Proc Logistic; the other way I created an interaction variable in DATA step. Both variables in the interaction term are categorical variables. Results are different when I included the missing in the analysis. One is significant, the other is not. Can't figure out why this will be different. Not sure how SAS deal with the interaction term in Proc Logistic. I have some questions. We were using a published case-controlled study data to do some analyses. We need to do conditional logistic regression, using the matching id as 'strata' variable. My instructor told me to use proc phreg to do the conditional logistic regression, following the way of the example found in SAS documentation. You can easily find it. In that example, the output gives estimated HR of the explorotary variables. Since we are doing the logistic regression, though we are using proc phreg, should we explain the 'HR' as Odd Ratio? Or it is just HR? I was told, the HR and OR are the same. I know in low probability, these two are approximately equal. But I feel their meaning are not the same. Why can we use the proc phreg to do the logistic regression? Or for what reason, we want to use proc phreg to do the conditional logistic regression? If I use the proc logistic to do the conditional logistic regression, will I get the same result? Sorry, I did options try it before. Apparent Bug In Proc Logistic Scoring kk This question is not related to the subject of the discussion, it should have been submitted as a new discussion. PG Read All 12 Posts. Modeling And Scoring Weighted Data With Proc Logistic a1 Hello, I am using PROC LOGISTIC to build a multinomial logistic model using dataset A and then score the second dataset B. Best regards, Konstantin Read All 1 Posts. Equivalent To Proc Logistic-Units Statement In Proc Genmod zp In Proc Logistic we can add 'Units" statement to change the unit of the explanatory variable. Thanks Read All 1 Posts. Goodness Of Fit In Binary Logistic Regression 1x Hi can any one help clarify doubt in goodness of fit in binary logistic. Goodness Of Fit In Binary Logistic Regression 1x The Hosmer-Lemeshow test is not my favorite test; it has low power in smaller samples and can show significance for important deviations in vary large ones. Doc Muhlbaier Duke Read All 2 Posts. Sign Test In Proc Phreg ax Hi, I want to compare the survival curve for a treatment and a control group. I would be very grateful if anyone can provide some help. Logistic Regression In Sas 38 I have the data below and here is my code to conduct logisic regression analysis. Logistic Regression In Sas 38 PGStats, since I am using Enterprise Guide 4. Read All 15 Posts. Diffrent Correlation Matrices Using Proc Corr And Corrb zj Hello, Can anyone provide me with the formula sas uses to calculate correlation coefficients using the corrb option in logistic regression procedure? Many Thanks, Read All 1 Posts. Cross Validation Of Logistic Regression Model 1j Hi. Cross Validation Of Logistic Regression Model 1j There is a bootstrap tool on the SAS support web site that works well. Check out this knowledgebase article: Stepwise Logistic Regression In Proc Logistic xk Hello everybody, I am in the process of learning the ins and outs of using PROC LOGISTIC to conduct stepwise logistic regression. Thank you for your time. Read All 1 Posts. Comparison 11 Dear all I'm using proc logistic to calculate odds ratio. First I tried running three logistic as follow: Then I tried with: What can I do to calculate all the odds ratio I need in the correct way? Thank in advance for any answer. Comparison 11 Thank you very much!! Read All 3 Posts. Statement Is Not Valid Error When Using The Slice Statement In Proc Logistic dd Hi, Can someone give me the position of the Slice Statement in Proc Logistic syntax? Error When Using The Slice Statement In Proc Logistic dd Unless you are operating on kkd version earlier than 9. Steve Denham Read All 6 Posts. Changing Plot Titles And Axes From Default Values While Using Proc Logistic x8 I'm new to SAS and I am currently processing a large number of plots using the proc logistic procedure. Surveylogistic, Logistic And Weight sc Hi, I have two questions about surveylogistic procedure and weight statement. First, I am doing analysis national data by using logistic regression binary dependent. I really wonder about weight statement's meaning in SAS. And I really hope your help and opinion!! Surveylogistic, Logistic And Weight sc Hi, Sampling weights are used to calibrate parameter estimates calculated based on a sample. Hope this helps, Thanks, Read All 5 Posts. Proc Logistic Vs Gui ks I'm doing some logistic regression analysis in EG 4. Proc Logistic Vs Gui ks Of course, I forgot about the code hooks. Proc Logistic dc Hello, It's me again. I've done some proc logistic for a while. If the model adjusted the data perfectly, the table should be diagonal. So it's a good measure of the quality of the model. How can I do that? Proc Logistic dc What you are looking to is called "classification table". Read All 2 Posts. Proc Logistic Output Query ak Hi All, I am working with Proc Logistic and I am using the Stepwise process. Thanks a lot in advance!! Proc Logistic Output Query ak I think you can use the ODS TRACE option to get this. Then rerun the proc logistic and use the ODS statement to turn the output into data: Proc Logistic And New Independent Value Inputs And Corresponding Output aj Hi, I fitted an ordered logistic model using Proc Logistic, and now want to feed in a new set of independent variables values to the model coefficients. After I save the coefficients from Proc Logistic,Is there a quick, off the shelf way to do that? Robust Logistic Regression sf Can anyone help me with the sas code for robust logistic regression model? Thank you in advance! Wendy Read All 1 Posts. How To Output The Standard Error Of Prediction In Proc Logistic? Linear Predictor, Predicted Probability, and Confidence Limits" section of the Regression documentation: How To Avoid Trimmed Variable Name pz Anybody have any tricks to avoid the output from PROC LOGISTIC, especially in the "Analysis of Maximum Likelihood Estimates" section. Sometimes, I have multiple variables such as: It will trim them off at a certain length Example of my code: How To Avoid Trimmed Variable Name pz That's sas what I needed. Help -- Exact Logistic Regression 33 Hi everyone, I am using the PROC LOGISTIC to conduct exact logistic regression. Many thanks for your help! Zhuoqiao Read All 1 Posts. Error Message In Proc Logistic pp I'm trying to run a model using Proc Logistic but I get an error message saying "no valid observations". Error Message In Proc Logistic pp I am not sure if this is something that you have thought about but it may be possible that people with answers to one of your indicator variables may not have responses to another variable. Hope this helps, if not I can look deeper. Proc Logistic - Variable Problem kj So i'm using proc logistic and a little confused. Proc Logistic - Variable Problem kj Name the categorical predictor variables on a CLASS statement. Please Help Me Understand The Following Multiple Imputation Errors kz Hi, I am trying to do multiple imputation. The above message was for the following by-group: The data set WORK. COVBDAT has 10 observations and 4 variables. PARMSDAT has 10 observations and 7 variables. There were observations read from the data set ABX. PROCEDURE LOGISTIC used Total process time: Between-imputation variance is zero for variable intercept. Between-imputation variance is zero for variable cancer. PROCEDURE MIANALYZE used Total process time: The SAS System stopped processing this step because of errors. Please Help Me Understand The Following Multiple Imputation Errors kz I know this question was posted a few years ago, but I ran into the second problem listed here and thought I would post how I solved it in case anyone else runs into it. Code For A Table With Aic And Aicc In Proc Logistic sk Could anyone please forward me code for generating a table with AIC and AICc values in Proc logistic in SAS 9. Code For A Table With Aic And Aicc In Proc Logistic sk OK Thanks for getting me this far! Read All 12 Posts. Gini Coefficient In Proc Logistic js dear all, how to display the gini coefficient value in output output of proc logistic? Gini Coefficient In Proc Logistic js or have a look here - but it gives the same result https: Proc Logistic jc does anyone know how to export the "c" and the "pval" from proc logistic??? Thanks in advance CL. Proc Logistic jc thanksyou first reply "ods trace on" is what i needed! Questions On Proc Logistic, K-Fold Cross Validation, Auc. Please, suggest right approach for probably standard modelling task below. In PROC LOGISTIC, is there way to specify AUC or c-statistics? In PROC LOGISTIC, is there way to specify internal k-fold self-split cross-validation in dataset 3. I found several relevant articles, but not a direct example: SAS Programming for Data Mining: AUC calculation using Wilcoxon Rank Sum Test - ROC analysis for binary response models fit in the GLIMMIX, NLMIXED, GAM or other procedures - ROC analysis using validation data and crossvalidation http: Your links will definitely help me to use solid existing code and not to invent bicycle: Using Proc Logistic As Check For Chi-Square xz I ran some chi-square tests for a binary dependent variable and other binary independent variables. Here's my code for chi-square and proc logistic: Using Proc Logistic As Check For Chi-Square xz Thanks Dave. Hosmer-Lemeshow Goodness Of Fit pp I am building a logistic regression model using PROC LOGISTIC with a sample data. Proc Logistic p9 It is very clearly described in the documentation on the SAS web site; look at the MODEL statement section. Message was edited by: Doc Duke Read All 2 Posts. Proc Genmod - Odds Ratio. Does anyone know if it is possible to run the previous example in EM? Do you know how to do it? Thanks for your help, Reynaldo. Thanks output your help, Reynaldo Read All 1 Posts. All my songs on Spotify sync to my iphone. Why cant I update past V6. Keep dropping connection on Moto SBu db: Radio en video db: Missing Bass Redirection Option for Sound Blaster Audigy. White Standard Errors z7 Hi I am trying to get white standard errors test in my logistic regression. I read a few articles on the internet and came up with the following code: Any idea what I'm doing wrong? White Standard Errors z7 Thanks for your quick response, Steve! That is very helpful. Regards, Devin Peipert Read All 10 Posts. Steve Denham Read All 2 Posts. How Options Find Outliers In Proc Logistic? Instrumental Variable And Cox Proportional Hazards Model c8 Dear all, I want to use an instrumental variable regression survival analysis, and I think the PROC SYSLIN is only for linear or logistic regression? I am thinking to use below method, is it correct? Thanks for your help! Instrumental Variable And Cox Proportional Hazards Model c8 Well, there should be a Wald chi-square test in the output for PROC PHREG for this variable. Steve Denham Read All 4 Posts. The warning I refer is: Thanks and happy around exp 7. Proc Logistic - Detecting Quasi-Complete Separation jc I like the Firth penalized ML method, but if that is not available due to prior decisions, I would try something like: Steve Denham Read All 3 Posts. Lr Statistic Test In Logistic Procedure xz How can i perform the LR statistic test in the Logistic Procedure instead of Wald test? How Does Sas Calculate 'Xbeta' Output In Proc Logistic? I am using censored data and the Heckman Two-Step method to run a regression analysis, so here's the dilemma: Regress binary censored variable eq 1 if censored, 0 otherwise on RHS variables. Thank you for your help. How Do I Use Either Proc Logistic Or Proc Genmod To Create A Logistic Model Without An Explanatory Variable? How To Get 8 Decimal Places For Parameter Estimates In Proc Logistic p8 Hi All, Please help me regarding this. How To Get 8 Decimal Places For Parameter Estimates In Proc Logistic p8 Kkd OlivierThanks for your reply. Please suggest regarding this. Read All 4 Posts. Exclusion From A Group From A Class Variable j3 Hello dear users, I am wondering if I cant just exclude one group from my class variable by the logistic regression I mean, if I have the variable age: Thank you proc logistic with grouped variables. Exclusion From A Group From A Class Variable j3 Ignoring other issues and given your coding, simply use a WHERE statement: Multicollinearity Diagnosis For Logistic Regression Using Proc Reg 13 I am running Proc Reg to check multicollinearity for logistic regression models. Multicollinearity Sas For Logistic Regression Using Proc Reg 13 With more than one categorical variable, I would run the collinearity diagnostics using k-1 dummy variables for the i-th categorical variable AND I would include the intercept. What Procedure To Use For Conditional Probability Table 9f Hello SAS community, I wanted to ask what SAS procedure would be adequate to make a conditional probability table. What Procedure To Use For Conditional Probability Table 9f Thank you Reeza for your insight Read All 7 Posts. Proc LogisticPlease Help. Thanks 3m Hi All, Just a quick one regarding proc logistic in SAS, I have entered 15 variables in my model and 14 variables seem to be good, does it mean that I should keep all of them in my model? Thanks 3m This seems to be an overfitting problem, I suggest check collinearity before adding variables in the analysis. Naeem Read All 5 Posts. Scoring Formula Using Proc Logistic Output 8x I have received the following output in Proc Logistic: PG Read All 2 Posts. Question On Testing For Serial Correlation In A Fixed Effects Logit Model 7s Hi: Dispersion Statistic In Proc Logistic. Should the pearson and deviance statistic only be used when subgrouping the observations? Am going around in circles with this so any advice would be much appreciated! Proc Logistic pc Dear all In the file attached you'll find an example of dataset I'm using. How can I proceed? Thanks in advance for any help. Proc Logistic pc try this http: PDF I just googled logistic regression repeated measures site: How Do Sas Compute Standard Error In Proc Logistic jm Please can some one explain to me how SAS compute standard error is proc logistic. How Do Sas Compute Standard Error In Proc Logistic jm Thanks Steve Read All 9 Posts. Scoring Data With Logit Model xs How can I get the Hosmer Lemesahaw Goodness of Fit test to work on scored data, i. To do this by guessing I ad a line of code: Here is the code I'm using in whole: Scoring Data With Logit Model xs Thanks! This is the answer I need. I have a followup inquiry: Greene confuses me even more with his remarks regarding maximum likelihood estimators: Classification Table Proc Logistic ad We could create a classification table in two ways: Classification Table Proc Logistic ad This may have been tacitly alluded to here, but I was thinking that SAS used a leave-one-out LOO method for calculating the SEN and SPEC in the ctable option. Proc Genmod fs Hello, I am analyzing case-control data collected from 4 different hospitals. Any help is greatly appreciated. Proc Logistic Predictor Variables kz Guys, I am trrying to do a logistic regression similar to: Proc Logistic Predictor Variables kz - ritam, just to clear things up the names of the variables actually dont matter. Proc Logistic Estimates 7f Hi all, After running a logistic kkd i get the output containing the estimates for the scoring variables. Proc Logistic Estimates 7f Hello, Chemicalab, Here is link to SAS STAT user guide that has some details on how to interpret proc logistic. Somers' D f9 The method of calculation may differ quite markedly for each procedure to allow for the functionality provided by the analysis.
Olaya for managing our society and letting us to do this thesis.
Uprooting the Leading Causes of Death, More than an Apple a Day, From Table to Able, and Food as Medicine.
Tony faces a myriad of immediate, stress-inducing crises at home, at work and from the law.