polycuts: Estimates Cut-point Parameters for Fitted repolr Model In repolr: Repeated Measures Proportional Odds Logistic Regression

Description

After fitting a model using `repolr`, function `polycuts` gives estimates and standard errors for the K-1 cut-point parameters, based on the polynomial model from the fit of `repolr`. Polynomial cut-point parameter estimates from the orginal model are also shown.

Usage

 `1` ```polycuts(object, digits = 3, robust.var = TRUE) ```

Arguments

 `object` is a model fitted using `repolr`. `digits` the number of decimal places to display in reported summaries. `robust.var` a logical variable: if `TRUE` standard errors are based on robust variance estimates, otherwise naive estimates are used.

Value

 `coef` polynomial parameter estimates from `repolr`. `poly` a vector of K-1 cut-point parameters. `order` the order of the polynomial.

Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```data(HHSpain) mod.0 <- repolr(HHSpain~Sex*Time, data=HHSpain, categories=4, subjects="Patient", times=c(1,2,5), corr.mod="uniform", alpha=0.5) summary(mod.0) mod.1 <- update(mod.0, poly=1) summary(mod.1) polycuts(mod.1) mod.2 <- update(mod.0, poly=2) summary(mod.2) polycuts(mod.2) ```

repolr documentation built on May 29, 2017, 12:11 p.m.