From a Sampling Precision Perspective, Skewness Is a Friend and Not an Enemy!

A New Way to Think About Internal and External Validity

Researchers have been concerned with internal and external validity for decades, and the discussion continues. The present proposal is that there are less important and more important senses in which one can interpret internal and external validity, and these can be integrated with a taxonomy that includes theoretical, auxiliary, statistical, and inferential assumptions. The integration sheds light on recent exchanges in the literature on validity and suggests that the vaunted internal-external validity trade-off is false for more important senses of internal and external validity; internal and external validity increase or decrease together when there is an emphasis on underlying theories. Finally, the integration implies the desirability of some changes in typical research advice and practice.

Ferritin in pediatric critical illness: a scoping review

This scoping review aimed to elucidate and summarize the predictive role of serum ferritin in critical pediatric illness. The Preferred Reporting Items for Systematic reviews and Meta-Analyses methodology was employed to conduct a scoping review of 5 databases (MEDLINE, CENTRAL, ProQuest, ScienceDirect, and Epistemonikos) from the date of inception through January 24, 2022. Primary research studies involving subjects aged <18 years and serum ferritin levels were screened and reviewed independently following an a priori defined protocol. Of the 1,580 retrieved studies, 66 were analyzed. Summary statistics of serum ferritin levels for overall and condition-specific studies were reported in 30 (45.4%) and 47 studies (71.2%), respectively. The normal range was defined in 16 studies (24.2%), whereas the threshold was determined in 43 studies (65.1%). A value of <500 ng/mL was most often the upper limit of the normal range. Serum ferritin as a numerical variable (78.9%) was usually significantly higher (80.8%) in the predicted condition than in controls, while as a categorical variable with preset thresholds, ferritin was a significant predictor in 84.6% of studies. A total of 22 predictive thresholds predicted mortality (12 of 46 [26.1%]), morbidity (18 of 46 [39.1%]), and specific (16 of 46 [34.8%]) outcomes in 15 unique conditions. Increased precision in serum ferritin measures followed by close attention to the threshold modeling strategy and reporting can accelerate the translation from evidence to clinical practice.

The Dark Tetrad, cybervictimization, and cyberbullying: The role of moral disengagement

Cyberbullying is a form of antisocial online behaviors. Perpetration of intentional and repeated harm inflicted through electronic devices is associated with dark personality traits and may be caused by morally impaired reasoning. In the current study, we investigated the associations between the Dark Tetrad (narcissism, Machiavellianism, psychopathy, sadism), cybervictimization, and cyberbullying. We also examined the intervening role of moral disengagement in the relationship between the Dark Tetrad and cyberbullying. Two hundred fifty-one adults (72.6% women) participated in an on-line study. Correlational analysis indicated that all dark personality traits were associated with higher cyberbullying and cybervictimization (except narcissism as a predictor of cybervictimization). Moral disengagement was positively related to Machiavellianism, sadism and cybervictimization. Controlled for covariance between the Dark Tetrad traits and cybervictimization, sadism and cybervictimization appeared to be associated with cyberbullying. Moreover, moral disengagement did not account for the associations between the Dark Tetrad and cyberbullying.

Statistical Assumptions and Reproducibility in Psychology: Data Mining Based on Open Science

The failures of reproducibility in psychology (or other social sciences) can be investigated by tracing their logical chains, from statistical hypothesis to their conclusion. This research starts with the normality hypothesis, the homoscedasticity hypothesis, and the robust hypothesis and uses the R language to simulate and analyze the original data of 100 studies in Estimating the Reproducibility of Psychological Science to explore the influence of the premise hypothesis on statistical methods on the reproducibility of psychological research. The results indicated the following: (1) the answer to the question about psychological studies being repeatable or not relates to the fields to which the subjects belonged, (2) not all the psychological variables meet the normal distribution hypothesis, (3) the t-test is a more robust tool for psychological research than the Analysis of Variance (ANOVA), and (4) the robustness of ANOVA is independent of the normality and variance congruence of the analyzed data. This study made us realize that the repeatable study factors in psychology are more complex than we expected them to be.

Information–Theoretic Aspects of Location Parameter Estimation under Skew–Normal Settings

In several applications, the assumption of normality is often violated in data with some level of skewness, so skewness affects the mean’s estimation. The class of skew–normal distributions is considered, given their flexibility for modeling data with asymmetry parameter. In this paper, we considered two location parameter (μ) estimation methods in the skew–normal setting, where the coefficient of variation and the skewness parameter are known. Specifically, the least square estimator (LSE) and the best unbiased estimator (BUE) for μ are considered. The properties for BUE (which dominates LSE) using classic theorems of information theory are explored, which provides a way to measure the uncertainty of location parameter estimations. Specifically, inequalities based on convexity property enable obtaining lower and upper bounds for differential entropy and Fisher information. Some simulations illustrate the behavior of differential entropy and Fisher information bounds.

Social Networks Addiction (SNA-6) - Short: Validity of Measurement in Mexican Youths

The excessive use of social networks needs to be addressed, and this phenomenon needs to be measured for the purpose of evaluation, prevention, and intervention among adolescents and young people. The objective of the study was to adapt and psychometrically validate the Brief Scale of Addiction to Social Networks (SNA-6) among Mexican adolescents and young adults. The participating sample consisted of 2,789 students from 6 public educational campuses in Cuernavaca (Morelos, Mexico). Data collection was carried out through a web platform to strictly maintain anonymity, voluntary participation, and confidentiality. Data analysis first focused on the detection of possible response biases (random intercept model and careless/insufficient effort), the quality of the response structure partial credit model (PCM), dimensionality (CFA and invariance), and the relationship with external variables. It was found that when the range of efficient response options was limited to less than five, reliability was high (0.91), and unidimensionality was maintained. Response biases slightly affected the dimensional structure of the instrument. Measurement invariance reached scalar invariance in the sex, age, and campus groups. The association with sensation seeking and depression, controlling for sex and age covariates, was statistically significant, small, and theoretically consistent. Implications of the results are discussed.

A Viable Approach to Mitigating Irreproducibility

In a recent article, Trafimow suggested the usefulness of imagining an ideal universe where the only difference between original and replication experiments is the operation of randomness. This contrasts with replication in the real universe where systematicity, as well as randomness, creates differences between original and replication experiments. Although Trafimow showed (a) that the probability of replication in the ideal universe places an upper bound on the probability of replication in the real universe, and (b) how to calculate the probability of replication in the ideal universe, the conception is afflicted with an important practical problem. Too many participants are needed to render the approach palatable to most researchers. The present aim is to address this problem. Embracing skewness is an important part of the solution.

The doctrine of normal tendency in active learning teaching methodology: investigations into probability distributions and averages

Traditional lecture and active learning methods of teaching a university course are compared. The particular course is university calculus. The lecture method was applied to two sections of calculus. The active learning method was applied to two other sections. In all cases students were given an examination near the beginning of the course and a final examination at the end of the course. The score averages for the active learning method were higher than for the lecture method. The distribution of scores for the lecture method were non-normal multimodal in the first and final examinations. The distribution for the active learning method went from non-normal multimodal in the first examination to unimodal normal in the final examination. A new undeceivable nature evidence-based method is presented for measuring teaching efficacy by probability distribution.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s43545-021-00154-1.

The inaccuracy of sample-based confidence intervals to estimate a priori ones

Confidence intervals (CIs) constitute the most popular alternative to widely criticized null hypothesis significance tests. CIs provide more information than significance tests and lend themselves well to visual displays. Although CIs are no better than significance tests when used solely as significance tests, researchers need not limit themselves to this use of CIs. Rather, CIs can be used to estimate the precision of the data, and it is the precision argument that may set CIs in a superior position to significance tests. We tested two versions of the precision argument by performing computer simulations to test how well sample-based CIs estimate a priori CIs. One version pertains to precision of width whereas the other version pertains to precision of location. Using both versions, sample-based CIs poorly estimate a priori CIs at typical sample sizes and perform better as sample sizes increase.

Making the A Priori Procedure Work for Differences Between Means

Previous researchers have proposed the a priori procedure, whereby the researcher specifies, prior to data collection, how closely she wishes the sample means to approach corresponding population means, and the degree of confidence of meeting the specification. However, an important limitation of previous research is that researchers sometimes are interested in differences between means, rather than in the means themselves. To address this limitation, we propose additional equations that expand the a priori procedure to handle differences between means, both in matched and in independent samples. Finally, implications are discussed.

The sampling precision of research in five major areas of psychology

After obtaining a sample of published, peer-reviewed articles from journals with high and low impact factors in social, cognitive, neuro-, developmental, and clinical psychology, we used a priori equations recently derived by Trafimow (Educational and Psychological Measurement, 77, 831-854, 2017; Trafimow & MacDonald in Educational and Psychological Measurement, 77, 204-219, 2017) to compute the articles' median levels of precision. Our findings indicate that developmental research performs best with respect to precision, whereas cognitive research performs the worst; however, none of the psychology subfields excelled. In addition, we found important differences in precision between journals in the upper versus lower echelons with respect to impact factors in cognitive, neuro-, and clinical psychology, whereas the difference was dramatically attenuated for social and developmental psychology. Implications are discussed.

A Frequentist Alternative to Significance Testing, p-Values, and Confidence Intervals

There has been much debate about null hypothesis significance testing, p-values without null hypothesis significance testing, and confidence intervals. The first major section of the present article addresses some of the main reasons these procedures are problematic. The conclusion is that none of them are satisfactory. However, there is a new procedure, termed the a priori procedure (APP), that validly aids researchers in obtaining sample statistics that have acceptable probabilities of being close to their corresponding population parameters. The second major section provides a description and review of APP advances. Not only does the APP avoid the problems that plague other inferential statistical procedures, but it is easy to perform too. Although the APP can be performed in conjunction with other procedures, the present recommendation is that it be used alone.