Procedures for Two-Sample Comparisons with Multiple Endpoints Controlling the Experimentwise Error Rate

Biometrics ◽  
1991 ◽  
Vol 47 (2) ◽  
pp. 511 ◽  
Author(s):  
Walter Lehmacher ◽  
Gernot Wassmer ◽  
Peter Reitmeir
Keyword(s):  
Error Rate ◽  
Multiple Endpoints ◽  
Experimentwise Error Rate

Simultaneous Multiple Comparison Procedures in Psychiatric Research

1986 ◽  
Vol 20 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Wayne Hall ◽  
Kevin D. Bird
Keyword(s):  
Analysis Of Variance ◽  
Error Rate ◽  
Psychiatric Research ◽  
Experimentwise Error Rate ◽  
Research Designs ◽  
Dependent Variables ◽  
Post Hoc ◽  
Linear Contrasts ◽  
Multiple Comparison Procedures

Methods are presented for using linear contrasts to make inferences about differences between the means of several populations on continuous dependent variables. These methods control the experimentwise error rate (the probability of committing one or more type 1 errors in the set of decisions made within the experiment) for linear contrasts which compare some sub-sets of populations with others. Appropriate methods are outlined for testing contrasts which have been planned (i.e., specified independently of the data on which they are tested) and defined post hoc (i.e., after an inspection of the data). We show how these methods can be adapted to the analysis of data from factorial analysis of variance research designs.

A General Experimentwise Error Rate for Multiple Significance Tests

1976 ◽  
Vol 43 (3_suppl) ◽  
pp. 1263-1277 ◽  
Author(s):  
Stanley J. Rule
Keyword(s):  
Error Rate ◽  
Current Method ◽  
Fundamental Importance ◽  
Type I ◽  
Significance Tests ◽  
Type I Errors ◽  
Systematic Method ◽  
Experimentwise Error Rate ◽  
Comparison Error ◽  
Definition Of

No current method of controlling error rate is appropriate for all experiments. When the error rate is set at traditional levels a per comparison error rate can yield too high a proportion of Type I errors, while an experimentwise error rate can be too conservative because the purpose of the experiment is not taken into account. A definition of error rate is proposed in which the number of significant outcomes needed to answer the question of interest is considered and a distinction is made between tests of fundamental importance and those of only subsidiary interest. The definition provides a systematic method of unequally allotting the error rate such that more power is provided for tests of crucial interest and for experiments in which several significant results are required.

Note on Familywise Error Rates

1973 ◽  
Vol 32 (3_suppl) ◽  
pp. 1221-1222
Author(s):  
John D. Williams
Keyword(s):  
Error Rate ◽  
Error Rates ◽  
Alternative Procedure ◽  
Experimentwise Error Rate ◽  
Familywise Error Rates ◽  
Entire Experiment

An alternative procedure to the use of familywise error rates is described that retains an experimentwise error rate for the entire experiment. The procedure uses Dunn's (1961) test, considering each source of variation as a planned contrast and testing for significance with Dunn's tables.

scholarly journals Alternative to Tukey test

2020 ◽  
Vol 44 ◽  
Author(s):  
Ben Dêivide de Oliveira Batista ◽  
Daniel Furtado Ferreira
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Error Rate ◽  
The Other ◽  
Multiple Comparison ◽  
Tukey Test ◽  
Experimentwise Error Rate ◽  
Other Hand ◽  
Multiple Comparison Procedures

ABSTRACT In order to search for an ideal test for multiple comparison procedures, this study aimed to develop two tests, similar to the Tukey and SNK tests, based on the distribution of the externally studentized amplitude. The test names are Tukey Midrange (TM) and SNK Midrange (SNKM). The tests were evaluated based on the experimentwise error rate and power, using Monte Carlo simulation. The results showed that the TM test could be an alternative to the Tukey test, since it presented superior performances in some simulated scenarios. On the other hand, the SNKM test performed less than the SNK test.

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