LRupdate: LRupdate

In rms: Regression Modeling Strategies

LRupdate

Description

Update Model LR Statistics After Multiple Imputation

Usage

LRupdate(fit, anova)

Arguments

fit	an rms fit object
anova	the result of processMI(..., 'anova')

Details

For fits from ⁠orm, lrm, orm, cph, psm⁠ that were created using fit.mult.impute with lrt=TRUE or equivalent options and for which anova was obtained using processMI(fit, 'anova') to compute imputation-adjusted LR statistics. LRupdate uses the last line of the anova result (containing the overall model LR chi-square) to update ⁠Model L.R.⁠ in the fit stats component, and to adjust any of the new R-square measures in stats.

For models using Nagelkerke's R-squared, these are set to NA as they would need to be recomputed with a new intercept-only log-likelihood, which is not computed by anova. For ols models, R-squared is left alone as it is sample-size-independent and print.ols prints the correct adjusted R-squared due to fit.mult.impute correcting the residual d.f. in stacked fits.

Value

new fit object like fit but with the substitutions made

Author(s)

Frank Harrell

See Also

processMI.fit.mult.impute(), Hmisc::R2Measures()

Examples

## Not run: 
a <- aregImpute(~ y + x1 + x2, n.impute=30, data=d)
f <- fit.mult.impute(y ~ x1 + x2, lrm, a, data=d, lrt=TRUE)
a <- processMI(f, 'anova')
f <- LRupdate(f, a)
print(f, r2=1:4)   # print all imputation-corrected R2 measures

## End(Not run)

rms documentation built on Sept. 12, 2023, 9:07 a.m.