Constructing Confidence Intervals for Effect Sizes in ANOVA Designs

Chen, Li-Ting; Peng, Chao-Ying Joanne

doi:10.22237/jmasm/1383278640

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…Bootstrapping was utilized for all analyses (with the exception of descriptive statistics) because it is a robust procedure that decreases the likelihood of bias in the parameter estimates, such as confidence intervals (Cumming, 2014; Wilcox, 2005). Bootstrapping was conducted with 1,000 iterations of the sampling procedure, and bias-corrected confidence intervals (95%, two-tailed) were calculated because they have been shown to lead to better estimates of upper and lower confidence interval limits (Chen & Peng, 2013).…”

Section: Methodsmentioning

confidence: 99%

Prevalence and Risk of Drugging Victimization Among Sexual Minority and Heterosexual College Students

Schramm

Swan

Lambdin

et al. 2017

Criminal Justice Review

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Drugging (i.e., administering someone a drug or alcohol without their knowledge or consent) is a problem with substantial consequences for college students. Although sexual minorities face greater rates of drugging risk factors (e.g., greater rates of binge drinking have been identified among sexual minorities), no prior study has examined the prevalence or risk of drugging in this population. We sought to (1) describe rates at which heterosexual and sexual minority college students (separated by gender) have been drugged and to assess (2) sexual minority status and (3) illicit drug use as risk factors for drugging victimization for male and female college students. Results revealed that, controlling for established drugging victimization risk factors, male sexual minority college students were 72.9% more likely to report drugging victimization than heterosexual males. No significant differences in rates of drugging victimization were found between sexual minority and heterosexual women. However, both genders had greater drugging victimization among students who engaged in illicit drug use, binge drinking, and Greek life membership. These findings suggest that initiatives to promote the well-being of college students (e.g., sexual assault prevention) should include drugging as a focus, with outreach particularly to women and sexual minority men.

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Section: Methodsmentioning

confidence: 99%

Prevalence and Risk of Drugging Victimization Among Sexual Minority and Heterosexual College Students

Schramm

Swan

Lambdin

et al. 2017

Criminal Justice Review

View full text Add to dashboard Cite

show abstract

“…For the BCa CIs, we modified the SAS program written by Barker (2005). A demonstration of BCa CIs and the other two is published in Chen and Peng (2013). The nominal CI for all intervals was set at 0.95.…”

Section: Factors Manipulatedmentioning

confidence: 99%

The sensitivity of three methods to nonnormality and unequal variances in interval estimation of effect sizes

Chen

Peng

2014

Behav Res

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Confidence interval (CI) estimation for an effect size (ES) provides a range of possible population ESs supported by data. In this article, we investigated the noncentral t method, Bonett's method, and the bias-corrected and accelerated (BCa) bootstrap method for constructing CIs when a standardized linear contrast of means is defined as an ES. The noncentral t method assumes normality and equal variances, Bonett's method assumes only normality, and the BCa bootstrap method makes no assumptions. We simulated data for three and four groups from a variety of populations (one normal and five nonnormals) with varied variance ratios (1, 2.25, 4, 8), population ESs (0, 0.2, 0.5, 0.8), and sample size patterns (one equal and two unequal). Results showed that the noncentral method performed the best among the three methods under the joint condition of ES = 0 and equal variances. Performance of the noncentral method was comparable to that of the other two methods under (1) equal sample size, unequal weight for each group, and the last group sampled from a leptokurtic distribution, or (2) equal sample size and equal weight for all groups, when all are sampled from a normal population, or only the last group sampled from a nonnormal distribution. In the remaining conditions, Bonett's and the BCa bootstrap methods performed better than the noncentral method. The BCa bootstrap method is the method of choice when the sample size per group is 30 or more. Findings from this study have implications for simultaneous comparisons of means and of ranked means in between- and within-subjects designs.

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Null Hypothesis Significance Testing,p-values, Effects Sizes and Confidence Intervals

Perdices

2017

Brain Impairment

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There has been controversy over Null Hypothesis Significance Testing (NHST) since the first quarter of the 20th century and misconceptions about it still abound. The first section of this paper briefly discusses some of the problems and limitations of NHST. Overwhelmingly, the ‘holy grail’ of researchers has been to obtain significantp-values. In 1999 the American Psychological Association (APA) recommended that if NHST was used in data analysis, then researchers should report effect sizes (ESs) and their confident intervals (CIs) as well asp-values. The APA recommendations are summarised in the next section of the paper. But as neuropsychological rehabilitation clinicians, the primary interest is (or should be) to determine whether or not the effect of an intervention is clinically important, not just statistically significant. In this context, ESs and their CIs provide information relevant to clinicians. The next section of the paper reviews common ESs and worked out examples are provided for the calculation of three commonly used ES (Cohen'sd, Hedge'sgand Glass’delta). Web-based resources for calculating other ESs and their CIs are also reviewed.

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Constructing Confidence Intervals for Effect Sizes in ANOVA Designs

Cited by 4 publications

References 23 publications

Prevalence and Risk of Drugging Victimization Among Sexual Minority and Heterosexual College Students

Prevalence and Risk of Drugging Victimization Among Sexual Minority and Heterosexual College Students

The sensitivity of three methods to nonnormality and unequal variances in interval estimation of effect sizes

Null Hypothesis Significance Testing,p-values, Effects Sizes and Confidence Intervals

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