Impact of unbalancedness and heteroscedasticity on classic parametric significance tests of two-way fixed-effects ANOVA tests

Impact of unbalancedness and heteroscedasticity on classic parametric significance tests of two-way fixed-effects ANOVA tests

Classic parametric statistical tests, like the analysis of variance (ANOVA), are powerful tools used for comparing population means. These tests produce accurate results provided the data satisfies underlying assumptions such as homoscedasticity and balancedness, otherwise biased results are obta...

Full description

Bibliographic Details
Main Author: Chaka, Lyson
Other Authors: Muchengetwa, S.
Format: Others
Language:en
Published: 2017
Subjects:
Fixed-effects analysis of variance
Unbalancedness
Heteroscedasticity
Homoscedasticity
Effect size
Eta-squared
Traditional F-tests
Robust tests
Normality
Outliers
Shapiro Wilk’s tests
519.538
Analysis of variance
Regression analysis
Multivariate analysis
Mathematical statistics
Online Access:Chaka, Lyson (2016) Impact of unbalancedness and heteroscedasticity on classic parametric significance tests of two-way fixed-effects ANOVA tests, University of South Africa, Pretoria, <http://hdl.handle.net/10500/23287>
http://hdl.handle.net/10500/23287

Internet

Chaka, Lyson (2016) Impact of unbalancedness and heteroscedasticity on classic parametric significance tests of two-way fixed-effects ANOVA tests, University of South Africa, Pretoria, <http://hdl.handle.net/10500/23287>
http://hdl.handle.net/10500/23287

Similar Items