stab_single function

Function to evaluate bootstrap predictor and model stability.

stab_single Stability analysis of predictors and prediction models selected with the glm_bw.

stab_single(pobj, nboot = 20, p.crit = 0.05, start_model = TRUE)

Arguments

• pobj: An object of class smods (single models), produced by a previous call to glm_bw.
• nboot: A numerical scalar. Number of bootstrap samples to evaluate the stability. Default is 20.
• p.crit: A numerical scalar. Used as P-value selection criterium during bootstrap model selection.
• start_model: If TRUE the bootstrap evaluation takes place from the start model of object pobj, if FALSE the final model is used for the evaluation.

Returns

A psfmi_stab object from which the following objects can be extracted: bootstrap inclusion (selection) frequency of each predictor bif, total number each predictor is included in the bootstrap samples as bif_total, percentage a predictor is selected in each bootstrap sample as bif_perc and number of times a prediction model is selected in the bootstrap samples as model_stab.

Details

The function evaluates predictor selection frequency in bootstrap samples. It uses as input an object of class smods as a result of a previous call to the glm_bw.

Examples

model_lr <- glm_bw(formula = Radiation ~ Pain + factor(Satisfaction) + 
   rcs(Tampascale,3) + Age + Duration + JobControl + JobDemands + SocialSupport, 
   data=lbpmilr_dev, p.crit = 0.05)

## Not run:

 stab_res <- stab_single(model_lr, start_model = TRUE, nboot=20, p.crit=0.05)
 stab_res$bif
 stab_res$bif_perc
 stab_res$model_stab
## End(Not run)

References

Heymans MW, van Buuren S. et al. Variable selection under multiple imputation using the bootstrap in a prognostic study. BMC Med Res Methodol. 2007;13:7-33.

Sauerbrei W, Schumacher M. A bootstrap resampling procedure for model building: application to the Cox regression model. Stat Med. 1992;11:2093–109.

Royston P, Sauerbrei W (2008) Multivariable model-building – a pragmatic approach to regression analysis based on fractional polynomials for modelling continuous variables. (2008). Chapter 8, Model Stability. Wiley, Chichester.

Heinze G, Wallisch C, Dunkler D. Variable selection - A review and recommendations for the practicing statistician. Biom J. 2018;60(3):431-449.

http://missingdatasolutions.rbind.io/