J. Meca - Academia.edu (original) (raw)

Papers by J. Meca

Revista Iberoamericana De Fisioterapia Y Kinesiologia, Jun 1, 2003

Behavioral Psychology/Psicologia Conductual

Cited By (since 1996): 4, Export Date: 23 July 2012, Source: Scopus, CODEN: PCONF, Language of Or... more Cited By (since 1996): 4, Export Date: 23 July 2012, Source: Scopus, CODEN: PCONF, Language of Original Document: Spanish, Correspondence Address: Olivares, J.; Dpto. de Personalidad, Facultad de Psicología, Campus Universitario de Espinardo, Apdo. 4021, 30080 Espinardo, Murcia, Spain; email: jorelx@um.es, References: Albano, A.M., Detweiler, M.E., Logsdon-Conradsen, S., Cognitive-behavioral interventions with socially phobic children (1999) Handbook of Psychotherapies with Children and Families, pp. 255-280. , S. W. Russ T. H. Ollendick dirs. New York: Plenum;

Trauma, violence & abuse, Jan 26, 2014

In this systematic review, the effectiveness of psychological treatment interventions for child m... more In this systematic review, the effectiveness of psychological treatment interventions for child molesters was examined. Studies were restricted to randomized control trials (RCTs), controlled trials, and cohort designs where recidivism had been used as the outcome variable. ASSIA, NCJRS, Medline, PsychINFO, EMBASE, Pro-requests Dissertations and Theses A&I, and the Cochrane Library were searched. Ten experts were contacted and the reference lists of 12 systematic reviews and 40 primary studies were observed. The number of hits was 3,019, of which 564 duplicates, 2,388 irrelevant references, and 38 that did not meet the inclusion criteria were removed. Fourteen studies using mixed samples had to be omitted because it was not possible to determine the recidivism rates of child molesters in the samples described. One RCT and 9 cohort studies were included in the data synthesis, providing 2,119 participants. In all, 52.1% received the intervention under investigation and 47.9% did not. ...

The Spanish journal of psychology, 1999

When a primary study includes several indicators of the same construct, the usual strategy to met... more When a primary study includes several indicators of the same construct, the usual strategy to meta-analytically integrate the multiple effect sizes is to average them within the study. In this paper, the numerical and conceptual differences among three procedures for averaging dependent effect sizes are shown. The procedures are the simple arithmetic mean, the Hedges and Olkin (1985) procedure, and the Rosenthal and Rubin (1986) procedure. Whereas the simple arithmetic mean ignores the dependence among effect sizes, both the procedures by Hedges and Olkin and Rosenthal and Rubin take into account the correlational structure of the effect sizes, although in a different way. Rosenthal and Rubin's procedure provides the effect size for a single composite variable made up of the multiple effect sizes, whereas Hedges and Olkin's procedure presents an effect size estimate of the standard variable. The three procedures were applied to 54 conditions, where the magnitude and homogene...

Psychological Methods, 2014

… sobre prestación de …, 1996

Información del artículo Un modelo de entrenamiento de los componentes básicos para el procesamie... more Información del artículo Un modelo de entrenamiento de los componentes básicos para el procesamiento de la información en niños con ceguera y déficits visuales.

Psychological Methods, 2006

Journal of Educational and Behavioral Statistics, 2013

ABSTRACT Since heterogeneity between reliability coefficients is usually found in reliability gen... more ABSTRACT Since heterogeneity between reliability coefficients is usually found in reliability generalization studies, moderator analyses constitute a crucial step for that meta-analytic approach. In this study, different procedures for conducting mixed-effects meta-regression analyses were compared. Specifically, four transformation methods for the reliability coefficients, two estimators of the residual between-studies variance, and two methods for testing regression coefficients significance were combined in a Monte Carlo simulation study. The different methods were compared in terms of bias and mean square error (MSE) of the slope estimates, and Type I error and statistical power rates for the slope statistical tests. The results of the simulation study did not vary as a function of the residual variance estimator. All transformation methods provided negatively biased estimates, but both bias and MSE were reasonably small in all cases. In contrast, important differences were found regarding statistical tests, with the method proposed by Knapp and Hartung showing a better adjustment to the nominal significance level and higher power rates than the standard method.

Educational and Psychological Measurement, 2001

Five procedures for estimating a common risk difference in a set of independent 2 × 2 tables were... more Five procedures for estimating a common risk difference in a set of independent 2 × 2 tables were assessed via Monte Carlo simulation in terms of their bias, efficiency, confidence level adjustment, and statistical power. The maximum likelihood estimator showed the best performance, very closely followed by Cochran’s and Mantel-Haenszel’s procedures. The conditional weighted estimator, d CW, showed an irregular performace. The unweighted estimator, d U, showed less efficiency and statistical power than that of the other procedures. As a consequence, the use of the d CW and d U estimators is not recommended. The implications of the results in the practice of meta-analysis are discussed.

Educational and Psychological Measurement, 2010

Most of the statistical procedures in meta-analysis are based on the estimation of average effect... more Most of the statistical procedures in meta-analysis are based on the estimation of average effect sizes from a set of primary studies. The optimal weight for averaging a set of independent effect sizes is the inverse variance of each effect size, but in practice these weights have to be estimated, being affected by sampling error. When assuming a random-effects model, there are two alternative procedures for averaging independent effect sizes: Hunter and Schmidt’s estimator, which consists of weighting by sample size as an approximation to the optimal weights; and Hedges and Vevea’s estimator, which consists of weighting by an estimation of the inverse variance of each effect size. In this article, the bias and mean squared error of the two estimators were assessed via Monte Carlo simulation of meta-analyses with the standardized mean difference as the effect-size index. Hedges and Vevea’s estimator, although slightly biased, achieved the best performance in terms of the mean square...

Computational Statistics & Data Analysis, 2000

By Sanchez-Meca, Julio and Marin-Martinez, Fulgencio; Testing the significance of a common risk d... more By Sanchez-Meca, Julio and Marin-Martinez, Fulgencio; Testing the significance of a common risk difference in meta-analysis.

British Journal of Mathematical and Statistical Psychology, 1998