# RMS Describing, Resampling, Validating, and Simplifying the Model

**URL:** <https://discourse.datamethods.org/t/rms-describing-resampling-validating-and-simplifying-the-model/4790>\
**Category:** modeling strategy\
**Tags:** graphics, bootstrap, validation\
**Created:** [September 14, 2021, 7:24pm UTC](https://discourse.datamethods.org/t/rms-describing-resampling-validating-and-simplifying-the-model/4790 "2021-09-14T19:24:11Z")\
**Posts on this page:** 1\
**Showing post:** 137

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**Author:** ![FurlanLeo](https://discourse.datamethods.org/user_avatar/discourse.datamethods.org/furlanleo/32/3812_2.png) [@FurlanLeo](https://discourse.datamethods.org/u/FurlanLeo)\
**Post date:** [October 29, 2023, 12:44pm UTC](https://discourse.datamethods.org/t/rms-describing-resampling-validating-and-simplifying-the-model/4790/137 "2023-10-29T12:44:03Z")

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Thank you Professor!

Here are the results of my updated analysis.  
Please, any comments or suggestions for improving it?

1. **Chunk test / likelihood ratio chi-square test for added predictive value of the clinical measures altogether** :

```auto
# Chi-Square d.f. P 
# 6.386165e+01 7.000000e+00 2.545708e-11

```

1. **REV (500 bootstrap resamples of the full model)**:  

2. **Fit x4 model** :  
`lrm(formula = y ~ DOM + BAM + SEX + rcs(AGE, 3) + rcs(x4, 3),`  
`data = data, x = T, y = T)`

3. **Anova (Likelihood Ratio Statistics)**:  
Significant association of AGE (_df=2; p=0.0007_) and x4 (_df=2; p\<0.0001_)

4. **Bootstrap model and partial effects plots** :  

5. **Model validation with bootstrap (B=500)**:  
_Somer’s D_ (corrected index) = 0.5455

6. **Model calibration with bootstrap (B=500)**:  
_Mean absolute error_ = 0.014  
_0.9 Quantile of absolute error_ = 0.025  

7. **Nomogram** :

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