In this study, we explore the effects of non-normality and heteroscedasticity when testing the hypothesis that the regression lines associated with multiple independent groups have the same slopes. The conventional approach involving the F-test and the t-test (F/t approach) is examined. In addition, we introduce two robust methods which allow simultaneous testing of regression slopes. Our results suggest that the F/t approach is extremely sensitive to violations of assumptions and tends to yield misleading conclusions. The new robust alternatives are recommended for general use. © 2011 The British Psychological Society.link_to_subscribed_fulltex
Numerous authors suggest that the data gathered by investigators are not normal in shape. Accordingl...
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to t...
The classical procedures of comparing two groups, such as t-test are, usually restricted with the as...
In this study, we explore the effects of non-normality and heteroscedasticity when testing the hypot...
The robustness and power of nine strategies for testing the differences between two groups ’ regress...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
To deal with the problem of non-normality and heteroscedasticity, the current study proposes applyin...
The robustness and power of nine strategies for testing the differences between two groups’ regressi...
Methods exist for testing the homogeneity or group regression for the case in which there is only on...
It is well known that the conventional method for comparing j independent groups, one-way ANOVA F-te...
It is well known that the conventional method for comparing j independent groups, one-way ANOVA F-te...
UnrestrictedOrdinary least squares is one of the most popular approaches for fitting regression mode...
The study seeks to determine the effect upon the F-statistic of violating the assumption of homogene...
Numerous authors suggest that the data gathered by investigators are not normal in shape. Accordingl...
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to t...
The classical procedures of comparing two groups, such as t-test are, usually restricted with the as...
In this study, we explore the effects of non-normality and heteroscedasticity when testing the hypot...
The robustness and power of nine strategies for testing the differences between two groups ’ regress...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
This paper proposes two bootstrap-based tests that can be used to infer whether the individual slope...
To deal with the problem of non-normality and heteroscedasticity, the current study proposes applyin...
The robustness and power of nine strategies for testing the differences between two groups’ regressi...
Methods exist for testing the homogeneity or group regression for the case in which there is only on...
It is well known that the conventional method for comparing j independent groups, one-way ANOVA F-te...
It is well known that the conventional method for comparing j independent groups, one-way ANOVA F-te...
UnrestrictedOrdinary least squares is one of the most popular approaches for fitting regression mode...
The study seeks to determine the effect upon the F-statistic of violating the assumption of homogene...
Numerous authors suggest that the data gathered by investigators are not normal in shape. Accordingl...
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to t...
The classical procedures of comparing two groups, such as t-test are, usually restricted with the as...