Re: Proc Logistic / problems with Param = ref and param = effect Posted 03-23-2017 (8195 views) | In reply to Case The models under the two parameterizations are equivalent models, meaning they have the same log likelihood (-2LogL for Intercept and Covariates) and the same predicted values for any setting of the predictors. However, the CLASS statement enables you to fit a wider variety of models. PROC LOGISTIC: Traps for the unwary Peter L. Flom, Independent statistical consultant, New York, NY ABSTRACT Keywords: Logistic.

We’ll set up the problem in the simple setting of a 2×2 table with an empty cell.

Re: Oddsratio statement in proc logistic switches my reference group?

If you have an unbalanced replication of levels across variables or BY groups, then the design matrix and the parameter interpretation might be different from what you expect.

For procs logistic, genmod, phreg, and surveylogistic, you can use the ref= option, as follows: proc logistic data=ds; class classvar (param=ref ref="name-of-ref-group"); model y = classvar; run; Unfortunately, changing the reference in SAS is awkward for other procedures.

ods output ParameterEstimates=_PEst; proc logistic data=sashelp.class; class sex; model sex(ref="F") = Age Weight Height / expb ; run; 1 Like Reply.

proc logistic data =ds; class sex (ref='female'); model y = sex; run; SAS procedures that use this syntax: - PROC LOGISTIC - PROC GENMOD - PROC PHREG (for proportional hazards modeling of survival data)

If your response …

Each type of categorical variables requires different techniques to model its relationship with the predictor variables. PROC LOGISTIC Data=Injury_data Descending; Freq count; Class Driving Alcohol / Ref=First; Model Injury= Driving Alcohol Driving*Alcohol; RUN; • Default coding for LOGISTIC procedure • Can be specified with the PARAM=EFFECT option in the CLASS statement for some other procedures (e.g.

Some procedures in SAS allow you to directly set a reference group by simply including that information in the CLASS statement (see example below).

sammmy. proc logistic; /* Matches proc catmod and proc freq */ title3 'Sex by Outcome with proc logistic'; class sex / param=ref ref=last ; model outcome (ref='Pass') = sex / link=glogit; /* Generalized logits */ /* ref='Pass' is redundant because it's alphabetically the last anyway */ Gender: test sexFemale_Fail = sexFemale_Gone = 0; Proc Logistic Data = training outest=coeff descending; class rank / param = ref; Model admit = gre gpa rank / selection = stepwise slstay=0.15 slentry=0.15 stb; PROC LOGISTIC: The Logistics Behind Interpreting Categorical Variable Effects Taylor Lewis, U.S. Office of Personnel Management, Washington, DC ABSTRACT The goal of this paper is to demystify how SAS models (a.k.a, parameterizes) categorical variables in PROC LOGISTIC. Both simple and multiple logistic regression, assess the association between independent variable(s) (X i) — sometimes called exposure or predictor variables — and a dichotomous dependent variable (Y) — sometimes called the outcome or response variable.

However, the CLASS statement enables you to fit a wider variety of models. See The Logistic Procedure>Syntax>CLASS Statement>REF= for the word on this. The “Examples” section (page 1974) illustrates the use of the LOGISTIC procedure with 10 applications.

For example, in regression models you can evaluate the relative effect of each level on the response variable.

proc logistic data = hsb2m descending; class ses (ref='3') / param = ref ; model hiread = write ses ; run ; Looking at the output (below), the coding system shown in the "Class Level Information" section of the output is for two dummy variables, one for category 1 versus 3, and one for category 2 versus 3. For more examples and discussion on the use of PROC LOGISTIC, refer to Stokes, Davis, and Koch (1995) and to Logistic Regression Examples Using the SAS System. If you specify a 'label' in the ODDSRATIO statement, then the odds ratios produced by this statement are also labeled: 'label', 'label 2', 'label 3',…, and these are the labels used in the plots. Ordered Values are assigned to response levels in ascending sorted order (that is, the lowest response level is assigned Ordered Value 1, the next lowest is assigned Ordered Value 2, and so on) and are displayed in the "Response Profiles" table.

Posted 08-30-2012 (1399 views) | In reply to fetterbug Unfortunately, the ODDSRATIO statement did not honor the REF= level set by the CLASS statement until the current (SAS 9.3 TS1M2) release.

Here, we simply output three observations with three combinations of predictor and outcome, along with a weight variable which contains the case counts in each cell of the table

For example, the "Additive 1 vs 4" odds ratio says that the first additive has 5.017 times the odds of receiving a lower score than the fourth additive; that is, the first additive is 5.017 times more likely than the fourth additive to …

If a format is assigned to the variable, the ref= syntax requires the use of the formatted value. INTRODUCTION This paper covers some ‘gotchas’ in SASR PROC LOGISTIC.

PROC LOGISTIC initially parameterizes the CLASS variables by looking at the levels of the variables across the complete data set.

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