Robustness of the <i>T</i> Test: A Guide for Researchers on Effect of Violations of Assumptions

Havlicek, Larry L.; Peterson, Nancy L.

doi:10.2466/pr0.1974.34.3c.1095

Cited by 65 publications

(35 citation statements)

References 10 publications

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“…Specifically, in the 1-day retest condition (all scoring modes), group means increased upon retest. Possibly serious violations of the assumptions that underlie the t-test (Havlicek & Peterson, 1974) prompted supplemental use of the Wilcoxon matched pairs signed ranks test (Siegel, 1956) to assess differences in S's test-retest scores in each condition. With alpha set at p <.01, none of the 12 comparisons achieved significance.…”

Section: Distribution Of Item Responses and Test Scoresmentioning

confidence: 99%

Evaluation of the Michigan Alcoholism Screening Test (MAST) in assessing lifetime and recent problems

Zung

1982

J. Clin. Psychol.

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Investigated the reliability, validity and dimensionality of scores obtained by acute psychiatric inpatients (N = 120) on the Michigan Alcoholism Screening Test adapted to assess lifetime and current symptomatology. Under most conditions, test scores and classifications were reasonably consistent over brief intervals and the underlying structure of test content was unidimensional. The test showed high sensitivity (88%), insufficient specificity (50%), and modest classification accuracy overall (58%) and thus underscored the problem of excessive false positives and/or an inadequate diagnosis as criterion.

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Section: Distribution Of Item Responses and Test Scoresmentioning

confidence: 99%

Evaluation of the Michigan Alcoholism Screening Test (MAST) in assessing lifetime and recent problems

Zung

1982

J. Clin. Psychol.

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“…More recently the justification has been based upon Monte Carlo experiments (Norton, 1953;Boneau, 1959;Havlicek & Peterson, 1974). In these a computer is used to set up hypothetical experiments in which samples are drawn randomly from populations which depart from normality, or differ in variance.…”

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confidence: 99%

The approximate randomization test as an alternative to the F test in analysis of variance

Still¹,

White²

1981

Brit J Math & Statis

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In experimental psychology i t is usually difficult to show that populations sampled meet the requirements for the use o f t or F tests, or even that they are similar to populations sampled in Monte Carlo experiments designed to demonstrate the robustness of these parametric tests. Consequently, a test which makes weaker requirements without sacrificing power or versatility should be preferred. It is shown that this is true of modified approximate randomization tests, which, like the randomization tests on which they are based, use observed scores to set up a sampling distribution. The tests are versatile, since they can be used on factorial designs of any complexity and the results of Monte Carlo experiments indicate that their power approximates that of the F test when the assumptions underlying the latter are met and is significantly greater when the populations sampled are made up of two normal distributions with different means. It is concluded that, where adequate computing facilities are available, the approximate randomization test is preferable to an F test for analysis of variance designs.Over the last 40 years or so analysis of variance and related parametric statistical techniques have been widely used in experimental psychology. The use of such techniques in psychology has often been criticized (Siegel, 1956;Bradley, 1968), and partly as a result of such criticisms non-parametric techniques are now also widely employed. Some writers have considered replacing null hypothesis testing with estimation and Bayesian methods (Edwards et al., 1963), and Sidman (1960) recommended dispensing with statistics altogether. Nevertheless statistical analysis remains an important part of most papers in experimental psychology. The analysis nearly always involves the test of a null hypothesis, and the test used is usually a parametric test (Student's t or F ) in conjunction with analysis of variance. The reasons are obvious. The experimental designs required by analysis of variance are well suited to experimental psychology since the effects of any number of independent variables and their interactions can be examined; and they are satisfyingly elegant, yet relatively simple to understand and apply. I n these respects, especially in point of versatility, and the possibility of examining the effects of several independent variables in a single experiment, analysis of variance has no rivals. But, if critics such as Bradley (1968) are correct, analysis of variance, notwithstanding its admirable positive features, should be used on psychological data with much greater caution than is the case. psychology? The most obvious and common criticism is that the assumptions underlying the use of the F test with analysis of variance are not met, or not known to be met, in psychological experiments. One pair of assumptions is that the populations from which the samples are drawn are normally distributed and have equal variances. In the early days of analysis of variance in psychology it was customary to carry out tests of normality...

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“…Table 3 contains the mean values for recidivists and non-recidivists, that is, for those who had been reconvicted in two years as compared with those who were not convicted within the two year time period. Differences have been tested using the t-test; in some cases, those where the variable is a count, the test is not strictly valid because the distribution is not normal, however, the t-test is known to be robust to departure from this assumption (Havlicek and Peterson, 1974). In general, the results are as expected.…”

Section: Those Reconvicted Compared With Those Not Reconvictedmentioning

confidence: 95%

Predicting recidivism in a scottish prison sample

Cooke

Michie

1998

Psychology, Crime & Law

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Robustness of the T Test: A Guide for Researchers on Effect of Violations of Assumptions

Cited by 65 publications

References 10 publications

Evaluation of the Michigan Alcoholism Screening Test (MAST) in assessing lifetime and recent problems

Evaluation of the Michigan Alcoholism Screening Test (MAST) in assessing lifetime and recent problems

The approximate randomization test as an alternative to the F test in analysis of variance

Predicting recidivism in a scottish prison sample

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