Beyond tests of significance: Estimating strength of effects in selected ANOVA designs.

Vaughan, Graham M.; Corballis, Michael C.

doi:10.1037/h0027878

Cited by 211 publications

(116 citation statements)

References 17 publications

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“…Instead of a set of parallel curves, the factorial plots are somewhat barrel shaped ( Figures 10C and 10D). To investigate whether these significant deviations affected the scale values, the relative magnitude of experimental effects ((()2) was calculated for a three-way mixed-model design (Vaughan & Corballis, 1969). Since the sizes of the experimental left X right effects were small (0.63% and 0.37% for the SD and LD conditions, respectively), the effect of the deviations from parallelism on the scale values is negli-whereas the change in the form ofthe stimulus-response relationship results from a change in judgment function.…”

Section: Resultsmentioning

confidence: 99%

Contextual effects in difference judgments

Schifferstein¹

1995

Perception & Psychophysics

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Manipulating stimulus spacing, stimulus frequency, or stimulus range usually affects intensity judgments. In six experiments, I investigated the locus of analogues of these contextual effects in a "difference" estimation task. When all stimuli elicited the same taste quality, stimulus distribution affected the scale values only when water was included in the stimulus set (Experiments 1-3). When the subjective ranges of two taste qualities were manipulated, different scale values were obtained for the separate qualities in the two conditions (Experiment 4). Manipulation of the expected response distribution did not affect the scale values or the responses (Experiments 5-6). It is concluded that shifts in stimulus distributions or stimulus ranges result in shifts in subjective scale values. The contextual effects can be interpreted as relative shifts of a number of gustatory continua, with water lying on a separate continuum. Proposed is a model for context-dependent judgments, consisting of four stages: stimulus classification, stimulus placement, continuum placement, and continuum projection.

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Section: Resultsmentioning

confidence: 99%

Contextual effects in difference judgments

Schifferstein¹

1995

Perception & Psychophysics

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“…For designs involving more than one random independent variable the formulas provided by Vaughan and Corballis (1969) or Dodd and Schultz (1973) would be useful or the appropriate statistics may be derived using the expected mean squares reported in several popular intermediate statistics textbooks (e.g., Keppel, 1991;Kirk, 1982;Maxwell & Delaney, 1990).…”

Section: Between-subjects Univariate Designsmentioning

confidence: 99%

“…In many applied research contexts sample sizes are not equal and are generally disproportionate. Vaughan and Corballis (1969) cautioned against the use of omega squared in these situations. Carroll and Nordholm (1975), however, found that in a single-factor design, unequal n had little effect on the estimation of Kelley's ε 2 or Hay's ω 2 if variances are equal, and with equal n heterogeneous variances had little impact on the estimation of these effect sizes.…”

Section: Cautionary Notesmentioning

confidence: 99%

Measures of Effect Size for Comparative Studies: Applications, Interpretations, and Limitations

Olejnik¹,

Algina

2000

Contemporary Educational Psychology

560

359

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Although dissatisfaction with the limitations associated with tests for statistical significance has been growing for several decades, applied researchers have continued to rely almost exclusively on these indicators of effect when reporting their findings. To encourage an increased use of alternative measures of effect, the present paper discusses several measures of effect size that might be used in group comparison studies involving univariate and/or multivariate models. For the methods discussed, formulas are presented and data from an experimental study are used to demonstrate the application and interpretation of these indices. The paper concludes with some cautionary notes on the limitations associated with these measures of effect size.

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“…Each set of data was analyzed by a modified unweighted means analysis of variance (Winer, 1971, Case II;Huitson, 1966). The magnitude of experimental effects was estimated by computation of w' (Vaughan & Corballis, 1969).…”

Section: Methodsmentioning

confidence: 99%

Frequency, duration, and speed of wheel running of rats as a function of age and starvation

Jakubczak¹

1973

Animal Learning and Behavior

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The purpose of this experiment was to determine whether age differences in amounts of wheel running of starved rats were due to the frequency of bursts of running, to the average duration of bursts, to speed, or to any combination of these parameters. The experiment was carried out according to a 3 by 2 by 2 mixed model design. The independent variables were age (67, 293, and 746 days old at the start of starvation), food deprivation (total starvation vs ad lib), and occasion of measurement (initial vs maximum activity). The dependent variables were number of wheel revolutions, number of bursts of activity, number of seconds of running per burst, and revolutions per secono. The results indicated that acutely starved rats run more often, for longer periods, and at higher speeds than do sated rats, and that with increased age rats run less often, for a shorter time, and at slower speeds.The purpose of this experiment was to determine whether age-dependent decrements in the amounts of daily wheel running of starved rats were due to differences in the frequency of bursts of running, to differences in the average duration of running, to differences in the speed of running, or to differences in any combination of these parameters. With increasing weight loss, the amount of wheel running of young starved rats increases to a maximum and then decreases shortly before death (Campbell, 1964). This pattern of running changes only quantitatively with increasing age. A previous experiment (Jakubczak, 1967) indicated that, independent of drive level, amounts of wheel running of starved rats decrease with increasing age. In that investigation, the cumulative total of wheel running of starved rats decrease with increasing age. In that investigation, the cumulative total of wheel revolutions during 24 h was used as the dependent variable. However, rats do not run continually during the 24·h period, but distribute their running in a number of episodes or bursts of running (Slonaker, 1912). More recently, Premack and Schaeffer (1963) found that during a 1-h sample of running, starvation increases the cumulative amount of wheel running of rats by increasing both the frequency and average duration of bursts of running, but has little effect on speed of running. Consequently, the age differences in the amounts of wheel running of starved rats (Jakubczak,

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Beyond tests of significance: Estimating strength of effects in selected ANOVA designs.

Cited by 211 publications

References 17 publications

Contextual effects in difference judgments

Contextual effects in difference judgments

Measures of Effect Size for Comparative Studies: Applications, Interpretations, and Limitations

Frequency, duration, and speed of wheel running of rats as a function of age and starvation

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