Osborne and Waters (2002) focused on checking some of the assumptions of multiple linear regression. In a critique of that paper, Williams, Grajales, and Kurkiewicz correctly clarify that regression models estimated using ordinary least squares require the assumption of normally distributed errors, but not the assumption of normally distributed…

A meta-analysis by Tran, Sanchez, Arellano, and Swanson (2011) of the published RTI literature found that the magnitude of effect size (ES) between responders and low responders at posttest was significantly moderated by the pretest ES and the type of dependent measure administered, whereas no significant moderating effects were found in the mixed…

Steinberg and Monahan's (2011) reanalysis of the Teen Media longitudinal survey of adolescents does not meet prevailing standards for propensity score analysis and therefore does not undermine the original conclusions of the Brown, L'Engle, Pardun, Guo, Kenneavy, and Jackson (2006) analysis. The media do matter in the sexual socialization of…

The conceptual structure account of semantic memory (CSA; L. K. Tyler & H. E. Moss, 2001) claims that feature correlation (the degree to which features co-occur) and feature distinctiveness (the number of concepts in which a feature occurs) interact with domains of knowledge (e.g., living vs. nonliving) such that the distinctive features of…

Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…

R. Kliegl, A. Nuthmann, and R. Engbert reported an impressive set of data analyses dealing with the influence of the prior, present, and next word on the duration of the current eye fixation during reading. They argued that outcomes of their regression analyses indicate that lexical processing is distributed across a number of words during…

Semipartial correlation is one of several ways of determining the relative importance of independent variables in a multiple regression analysis. A veteran teacher of statistics and related topics explains his reasons for avoiding semipartial correlations. (SV)

Hierarchial causal models are described as pictorial representations of multiple regression equations. These models are particularly helpful for three reasons: (1) the formulation of problems in a path analytic framework forces a degree of explicitness that is often not present in research reports that rely solely on regression; (2) they provide a…

The perfunctory use of factor scores in conjunction with regression analysis is inappropriate for many purposes. It is suggested that factoring methods are most suitable for independent variable sets when some consideration has been given to the nature of the domain, which is implied by the predictors. (Author/BW)

In their reply to our article, Greenwald, Rudman, Nosek, and Zayas offered comments on the use of their procedure relative to one that focuses on standard multiple regression (SMR) methods). Here we address five issues where we think a balance of perspective is called for: (a) issues of measurement, (b) the structuring and reporting of the…

Most of the variance in educational effectiveness studies is inexplicable in terms of influences that can be measured and controlled. Nevertheless, it is still possible to design educational policy that will function well under conditions of uncertainty. (Author/RLV)

This paper presents two major criticisms of the construct validity investigation of the McCarthy Scales of Children's Abilities conducted by Watkins and Wiebe (1980). The criticisms pertain to the nature of the data presented and the accuracy and appropriateness of the statistical procedures employed. (BS)

Suggests a critical methodological flaw in a study done about the relationship between the Bem Sex-Role Inventory and certain indices of self-disclosure (Stokes, et al.). Notes that multiple regression analysis was not performed in appropriate hierarchical fashion. Includes Stokes reply to the critique. (PAS)

Discusses the nature, power, and limitations of four multivariate techniques: factor analysis, multiple analysis of variance, multiple regression, and multiple discriminant analysis. Shows how decision trees assist in interpreting results. (SK)

This paper encourages the use of multiple logistic analysis in early intervention research, to assess the degree of association of multiple factors (such as subject or situational characteristics) with a dichotomous outcome (such as benefitting or not benefitting from an intervention) and to estimate the probability of each outcome. (JDD)