From d63b386c944aff20f2f95ce91d202ef3d0f2a73a Mon Sep 17 00:00:00 2001 From: "Documenter.jl" Date: Sun, 11 Aug 2024 02:24:49 +0000 Subject: [PATCH] build based on 60bbc53 --- dev/.documenter-siteinfo.json | 2 +- dev/index.html | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index 099a02c..dd623fa 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2024-08-10T02:21:33","documenter_version":"1.5.0"}} \ No newline at end of file +{"documenter":{"julia_version":"1.6.7","generation_timestamp":"2024-08-11T02:24:43","documenter_version":"1.5.0"}} \ No newline at end of file diff --git a/dev/index.html b/dev/index.html index 2e40f62..d48790d 100644 --- a/dev/index.html +++ b/dev/index.html @@ -183,4 +183,4 @@ # calculate p-value polrtest(house_null, cont; test=:score)
0.0001648743597587817

Step 3: Now suppose we want to test significance of another predictor, z1. We just need to call polrtest with z1 and the same fiited null model. No model fitting is needed.

For demonstration purpose, we generate z1 randomly. The score test p-value of z1 is, not suprisingly, large.

z1 = randn(nobs(house_null))
 polrtest(house_null, z1)
0.1673512522966108

Step 4: We can also test a set of precitors or a factor.

z3 = randn(nobs(house_null), 3)
-polrtest(house_null, z3)
6.709335149358069e-10
+polrtest(house_null, z3)
6.709335149358069e-10