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Table 3 Stepwise variable selection on dataset C

From: Predicting emergency department visits in a large teaching hospital

Variable Coefficient Standard error Significance level
Intercept 308.6042 44.3327 <.01
Monday 12.5382 1.0441 <.01
Friday 9.718 1.0134 <.01
Saturday − 8.5790 1.0223 <.01
Sunday − 11.0413 1.0386 <.01
Winter 4.6875 1.0734 <.01
Time trend (daily) 0.0066 0.0013 <.01
Carnival 8.1048* 4.2351 N.S.
Holiday − 14.0091 3.2413 <.01
Monday * Holiday − 9.2721 4.7393 N.S.
Sunday * Holiday 13.9759 5.0697 <.01
Summer vacation (week 1 + 2) − 12.1128 1.5751 <.01
Summer vacation (week 3 + 4) − 16.4741 1.6734 <.01
Summer vacation (week 5 + 6) − 6.4804 1.6781 <.01
Max temperature (in 0.1°C) 0.0196 0.0084 <.05
Global radiation (in J/cm2) 0.0038 0.0008 <.01
Max pressure (in 0.1 hPa) − 0.0210 0.0043 <.01
Max visibility (in 100m) − 0.0100 0.0044 <.05
Max humidity (in %) − 0.1357 0.0726 N.S.
Snow (in hours) − 0.7926 0.3286 N.S.
Fog (in hours) 0.4101 0.1583 <.01
Storm (in hours) − 0.8429 0.4619 N.S.
Observations 921
Multiple R-squared 0.4858
Adjusted R-squared 0.4738
  1. Dataset C is based on calendar variables plus weather predictions at the Jeroen Bosch Hospital (the refined set of predictors containing the best predictors of datasets A and B); * = interaction; N.S. not significant