Multiple comparisons in categorical data analysis.

Author: Rui CAO ¹ ; Jun QIAN ; Ping-yan CHEN
Author Information

1. Department of Biostatistics, School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Publication Type:Journal Article
MeSH: Data Interpretation, Statistical; Humans; Models, Statistical; Monte Carlo Method; Software; Statistics as Topic; methods
From: Journal of Southern Medical University 2010;30(1):118-120
CountryChina
Language:Chinese
Abstract:
OBJECTIVETo discuss the method for multiple comparisons of categorical data and propose an approach to deal with the percentage data.
METHODSThe method of multiple comparisons for percentages was verified based on Bonferroni methodology and Monte Carlo method using SAS 9.13 software.
RESULTSThe type I error could be enlarged if the statistical tests were conducted without adjustment of the significant level after dividing the data of several categories or percentages into several four-fold tables. For the percentage data, the correction of adjustment of the significant level was the number of pairwise comparison minus one, as supported by the results of Monte Carlo simulation.
CONCLUSIONMultiple comparisons of categorical data should be applied appropriately. Multiple comparisons of percentages data need to be conducted with the number of pairwise comparison minus one.