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This article reviews the procedure for item response theory (PROC IRT) procedure in SAS/STAT 14.1 to conduct item response theory (IRT) analyses of dichotomous and polytomous datasets that are unidimensional or multidimensional. The review provides an overview of available features, including models, estimation procedures, interfacing, input, and output files. A small-scale simulation study evaluates the IRT model parameter recovery of the PROC IRT procedure. The use of the IRT procedure in Statistical Analysis Software (SAS) may be useful for researchers who frequently utilize SAS for analyses, research, and teaching. [ABSTRACT FROM AUTHOR]

Barthel, Royston, and Parmar (2009, Stata Journal 9: 505-523) presented a menu-driven Stata program for calculating sample size and other design characteristics for a class of multiarm, multistage trials with time-to-event outcomes. In this article, we present several new features for the package. First, we allow hazard ratios greater than 1 to be targeted under the alternative hypothesis to make the design more widely applicable to other outcomes and disease areas. Second, we introduce new subroutines that use simulation to more accurately estimate the correlation between treatment effects at different stages and that calculate the familywise error rate, and we apply them to an example using the original design of the multiarm, multistage trial in prostate cancer. Finally, we present a new design of the dialog menu for nstage that improves its usability and incorporates options for calling the new subroutines. [ABSTRACT FROM AUTHOR]

Presents a FORTRAN subroutine to calculate a generalized measure of agreement between multiple raters and a set of correct responses at any level of measurement as studied by Colorado State University. Background information regarding the agreement; Views on subroutine; Subroutine language; Availability of subroutine ASTAND.

Presents subroutine AGREE to calculate a generalized measure of agreement for multiple judges and responses at any level of measurement. Subroutine; Computer and subroutine language; Capabilities and limitations of subroutine; Availability of subroutine.

The article discusses how to pass temporary variables to subprograms when programming in Stata computer language. It suggests breaking up larger programs into smaller subroutines to keep longer programs organized and make it more easier to write, debug, and maintain. It mentions using command such as tempvar or tempname in main program and passing it to the subroutine.

The article offers tips for certifying subroutines in the statistical software Stata. Suggestions include copying the subroutine and storing it in its own file, running the ado-file, and debugging a subroutine. Running a certification scrip is deemed useful when writing one's program in Stata. The use of program dir is also mentioned when running ado-file.