From 7d80543dbea8a09175096138ab757a8b8c11e525 Mon Sep 17 00:00:00 2001 From: acp29 Date: Sat, 6 Jan 2024 01:03:48 +0000 Subject: [PATCH] clarified documentation in demo 6 of `bootlm` --- inst/bootlm.m | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/inst/bootlm.m b/inst/bootlm.m index 907cbd92..075c7e71 100755 --- a/inst/bootlm.m +++ b/inst/bootlm.m @@ -2079,9 +2079,11 @@ %! ## we might rather consider the hypotheses tested using type II sums-of- %! ## squares without the interaction, which do not depend on the order and have %! ## more power respectively. This is easy to achieve with 2 predictors, by -%! ## repeating the two 'bootlm' commands above without the interaction (i.e. -%! ## setting 'model', 'linear') and taking the second p-value from the ANOVA -%! ## tables. For example: +%! ## repeating the 'bootlm' commands with different predictors added last to +%! ## the model (as above) but without the interaction (i.e. setting 'model', +%! ## 'linear'). We then take the statistics for the last main effect listed +%! ## in each of the ANOVA tables - these then correspond to the ANOVA test for +%! ## the respective predictor with type II sums-of-squares. For example: %! %! [~, ~, AOVSTAT1] = bootlm (salary, {degree, gender}, 'model', ... %! 'linear', 'display', 'off', 'varnames', ...