Cumulating Psychology: An Appreciation of Donald T. Campbell

Rosenthal, Robert

doi:10.1111/j.1467-9280.1991.tb00138.x

Cited by 21 publications

(5 citation statements)

References 19 publications

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“…Still taro growers and keepers of pigs, Samoans in recent years have incorporated U.S. development and employment programs into their economic system. Concise descriptions of the relevant sociocultural contexts can be found in R. L. Munroe and Munroe (1990a, 1990b, 1991) and R. H. Munroe, Munroe, Shwayder, & Arias (1997).…”

Section: Methods Samplesmentioning

confidence: 99%

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Aggression Among Children in Four Cultures

Munroe

Hulefeld²,

Rodgers³

et al. 2000

Cross-Cultural Research

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Behavioral aggression was observed among 192 3- to 9-year-old children in naturalistic settings in Belize, Kenya, Nepal, and American Samoa. Results showed that (a) boys exhibited aggression in approximately 10% of their social behaviors, girls in 6%, and in all four cultures the aggression of boys was more frequent than that of girls at a marginally significant level or better; (b) the aggression of boys occurred in the presence of large numbers (and proportions) of same-sex peers; (c) aggression declined with age; (d) only 5% of children’s aggressive interaction was directed toward adults (individuals aged 17 years or older), whereas 30% of their other, nonaggressive interaction was directed toward adults; (e) the presence of either parent tended to be associated with less aggression; and (f) aggression was displayed more frequently in the two patrilineal cultures (Kenya and Nepal) and less frequently in the other two cultures.

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Section: Methods Samplesmentioning

confidence: 99%

“…Although only one of our cultures exhibited significantly different male versus female aggression, we point out that in all four the difference did reach at least p < .10. It is perhaps appropriate to note Rosenthal's (1991) comment that "God loves the .06 nearly as much as the .05" (p. 220).…”

Section: Sex Differencesmentioning

confidence: 99%

Aggression Among Children in Four Cultures

Munroe

Hulefeld²,

Rodgers³

et al. 2000

Cross-Cultural Research

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“…Because science progress is obtained by cumulating evidence ( Rosenthal, 1991 ), scientists should also consider the secondary use of the data. With today’s electronic articles, there are no reasons for not including all of derived data: mean, standard deviations, effect size, CI, Bayes factor should always be included as supplementary tables (or even better also share raw data).…”

Section: What To Report and How?mentioning

confidence: 99%

Null hypothesis significance testing: a short tutorial

Pernet

2016

F1000Res

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Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices. Referee Status:Invited Referees Creative Commons Attribution Licence permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The author(s) declared that no grants were involved in supporting this work. The Null Hypothesis Significance Testing frameworkNHST is a method of statistical inference by which an experimental factor is tested against a hypothesis of no effect or no relationship based on a given observation. The method is a combination of the concepts of significance testing developed by Fisher in 1925 and of acceptance based on critical rejection regions developed by Neyman & Pearson in 1928. In the following I am first presenting each approach, highlighting the key differences and common misconceptions that result from their combination into the NHST framework (for a more mathematical comparison, along with the Bayesian method, see Christensen, 2005). I next present the related concept of confidence intervals. I finish by discussing practical aspects in using NHST and reporting practice. Fisher, significance testing, and the p-valueThe method developed by (Fisher, 1934; Fisher, 1955; Fisher, 1959) allows to compute the probability of observing a result at least as extreme as a test statistic (e.g. t value), assuming the null hypothesis of no effect is true. This probability or p-value reflects (1) the conditional probability of achieving the observed outcome or larger: p(Obs≥t|H0), and (2) is therefore a cumulative probability rather than a point estimate. It is equal to the area under the null probability distribution curve from the observed test statistic to the tail of the null distribution (Turkheimer et al., 2004). The approach proposed is of 'proof by contradiction ' (Christensen, 2005), we pose the null model and test if data conform to it.In practice, it is recommended to set a level of significance (a theoretical p-value) that acts as a reference point to identify significant results, that is to identify results that differ from the null-hypothesis of no effect. Fisher recommended using p=0.05 to judge whether an effect is significant or not as it is roughly two standard deviations away from the mean for the normal distribution (Fisher, 1934 page 45: 'The value for which p=.05, or 1 in 20, is 1.96 or nearly 2; it is convenient to take this...

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“…Contrast analysis was used to evaluate individual mean differences. To aid the reader in this evaluation, effect sizes (ES) of individual mean differences were reported based on Rosenthal's (1991) (3)…”

Section: Mclean and Hinrichsmentioning

confidence: 99%