SAS MACRO QIF
Download SAS MACRO QIF [package QIFv02.sas].
Enjoy the macro and notify us if you find any bugs in the code. Thanks.
Read a message from us [QIFv02.info].
Download SAS MACRO QIF manual [here].
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R PACKAGE QIF
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It contains two packages of R source code for Win 32 (.zip file) and
R source code for Win 64 (.zip file) for the QIF
that we developed for the estimation of regression coefficients in longitudinal
marginal models using quadratic inference functions. The first, qif_1.0-3.zip, works for Win 32 OS and the second, qif_1.0-4.zip, suits for Win 64 OS.
This R program is translated from the original SAS Macro QIF code. Visit site for related materials, including
the lecturenotes of a short course on QIF at the 2009 JSM and the dataset used in the following example.
- Step 0: Save the zip file in your computer.
- Step 1: Start the R software (version 2.9.0 or newer).
- Step 2: Click on the tab "packages" from the menu bar.
- Step 3: Click on "Install package(s) from local zip files ...".
- Step 4: Find the downloaded qif package from the opened dialogue window in step 3, and open the downloaded qif package zip file. R should then automatically install it, and the qif package is ready to be loaded after the installation is finished.
- The qif package works for several types of links: identity, log and logit; and it accommodates popular covariance structures such as independence, AR-1, compound symmetry and unstructured.
- The qif function outputs: estimates of the model parameters; asymptotic covariance matrix; standard errors and p-values for coefficients; model selection criteria AIC and BIC; number of iterations it takes for algorithm to converge; fitted values as well as residuals.
- The current version qif R package only supports equal cluster sized and equally spaced data type.
- out.ind <- qif(exacerbation ~ edss + treatment + time + duration + time2, id=id, data=exacerb, family=binomial, corstr="independence")
- out.ar1 <-qif(exacerbation ~ treatment + time + duration + time2, id=id, data=exacerb, family=binomial, corstr="AR-1")
- out.cs <- qif(exacerbation ~ treatment + time + duration + time2, id=id, data=exacerb, family=binomial, corstr="exchangeable")
- out.un <- qif(exacerbation ~ treatment + time + duration + time2, id=id, data=exacerb, family=binomial, corstr="unstructured")
Install QIF R Package
To install the downloaded qif package, follow the following 5 steps:Run QIF R Package
To load the R package, simply type "library(qif)" and "library(MASS)" into the R command window, the qif package is ready for use after this step.Examples
The marginal logistic model for Multiple Sclerosis Trial data. Trying four different types of covariance structures:Important Note: Matrix Inverse Function in QIF
The R package QIF provides two options of computing matrix inverse. The default is from Fortran math library, and the other one is generalized inverse "ginv" given in R library MASS. You can call option "ginv" through argument "invfun" in "qif()". For example, out.cs <- qif(exacerbation ~ treatment + time + duration + time2, id=id, data=exacerb, family=binomial, corstr="exchangeable", invfun="ginv") If this option is not specified, the default will be used. To see the full list of output options, use "names(CS)".| Top |
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GDEP: A Fortran Package for Gene Network Construction Based on Time Course Microarray Data(version 1.0 released on October, 08), download
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