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Programs, Data and Materials

Statistical Materials for Download

This is an R package for a survival analysis model that handles multi-type recurrent events. The methodological manuscript that describes the theory and applications of this model was published in the American Journal of Epidemiology and can be found here.

 Download

Biostatistical Methods: The Assessment of Relative Risks.

Biostatistical Methods (First Edition)

Biostatistical Methods (Second Edition)

Multivariate Rank Analysis. This is a SAS macro to implement the original Wei and Lachin (1984) multivariate Mann-Whitney analysis. The Macro also provides a number of different test statistics as described in Lachin (1992).Download. In August 2013 a minor discrepancy was detected between the program documentation and descriptions and how the output of the Mann-Whitney analysis was labeled. See the document readme.doc. The program was revised to correspond with the documentation.

References:

Wei LJ and Lachin JM. Two-sample asymptotically distribution-free tests for incomplete multivariate observations. Journal of the American Statistical Association, 1984, 79, 653-661. Thall PF and Lachin JM. Analysis of recurrent events: Nonparametric methods for random interval count data. Journal of the American Statistical Association, 1988, 83, 339-347. Lachin JM. Some large sample distribution-free estimators and tests for multivariate partially incomplete data from two populations. Statistics in Medicine, 11, 1151-1170, 1992.

Futility Assessment Based on Conditional Power

These are SAS programs to compute the properties of a futility assessment based on a conditional power computation as described in Lachin (2005). Download

Reference:

Lachin JM. A review of methods for futility stopping based on conditional power. Statistics in Medicine, 24, 2747-2764, 2005.

Futility Assessment Based on Interim Z-test Values.

These are SAS programs to implement a futility assessment based on a boundary on the interim Z-test value or a confidence limit as described in Lachin (2009). This does not require specification of a boundary on a conditional power value although the corresponding conditional power value is readily obtained. Download

Reference:


Lachin JM. Futility interim monitoring with control of type I and II error probabilities using the interim Z-value or confidence limit. Clinical Trials, 2009, 6:565-573.

Parametric Survival Models For Interval Censored Data With Time-Dependent Covariates.

This SAS program fits parametric regression model to interval censored event-time data with allowance for time-dependent covariates. The SAS macro and documentation are provided. Download programs, documentation, and SAS data set here.

Reference:

Sparling YH, Younes N, Lachin JM, and Bautista OM. Parametric survival models for interval-censored data with time-dependent covariates.Biostatistics;7, 599-614, 2006.

Robust Estimating Equations (REE).

This SAS Macro implements robust estimating equations for analyzing longitudinal data based on the methods developed by Hu and Lachin (2001). It includes GEE as a special option. The Levenberg-Marquardt algorithm has been used to improve convergence rates. This macro employs the same platform as the GEE macro developed by Ulrike Groemping (1993). The SAS macro and documentation are provided. Download

Reference:


Hu M and Lachin JM. Application of robust estimating equations to the analysis of quantitative longitudinal data, Statistics in Medicine, 20, 411-3428, 2001.

Sample Size and Power for a Logrank Test and Cox Proportional Hazards Model with Multiple Groups and Strata, or a Quantitative Covariate with Multiple Strata.

These are the SAS programs that performed the various computations presented in the Example section as described in Lachin (2013): Download.

Reference:


Lachin JM. Sample size and power for a logrank test and Cox proportional hazards model with multiple groups and strata, or a quantitative covariate with multiple strata. Statistics in Medicine 2013; 32:4413-4425. DOI: 10.1002/sim.5839.

Data Analysis Plan and Data Analysis Policy.

An outline of a data analysis plan that can be modified and adapted for individual use is given here: Download. An example of Data Analysis Policy is available here: Download.

Reference:


Best Practice: The Data Analysis Plan ? A Blueprint for Success. The American Statistical Association Conference on Statistical Practice February 20, 2015, New Orleans.

Optimal Screening Schedules For Disease Progression, With Application to Diabetic Retinopathy.

This is a technical report describing the statistical models employed for the net-benefit analysis in Nathan et al. (2016): Download. R code: Download. 


Reference:

Nathan DM, Bebu I, Hainsworth D, Klein R, Tamborlane W, Lorenzi G, Gubitosi-Klug R, Lachin JM. Establishing Rational individualized Screening Guidelines for Retinopathy in Type 1 Diabetes, submitted for publication, 2016.