Reading Predictors in Croatian

Phonological awareness (PA), rapid automatised naming (RAN) and working memory (WM) are considered to be the most important factors supporting reading development. However, their relative importance varies across orthographies and age. The goal of this study was to examine reading predictors in Croatian, a language with highly transparent orthography, after three years of formal reading instruction. The study included 80 participants (mean age: 10.07 years). Reading rate and accuracy were measured using lists of words and pseudowords, and PA was measured using phoneme deletion, phoneme addition and spoonerism tasks. RAN was measured using naming of colours, and WM was measured using the WM standardised measure of digit span (WISC-IV-HR) and pseudoword repetition. In order to find the best predictors of reading rate and accuracy for both words and pseudowords, three-stage hierarchical multiple regression was conducted. The results showed that in highly transparent language when reading is automatised, RAN is the most significant predictor of both reading rate and accuracy. Although this study did not show dissociation between the predictors supporting reading speed and reading accuracy, it confirmed the importance of PA as a suppressor variable for RAN in predicting pseudowords reading time.

Can Social Desirability Be Detected Statistically at the Macro-Sociological Level?

While a few have argued that social science has been subject to progressive biases, others have discounted such ideas. However, no one has yet performed empirical tests over a large range of studies for such possible bias, which we label macro-level social desirability (MLSD). Combining the results from fifty-nine empirical studies that assessed rates of nonheterosexuality among children of same-sex parents, we found that the higher the maximum rates reported, the less likely those reports were to have been cited in Google Scholar by counts or by annual rate, which may reflect MLSD. However, after several statistical controls, the association for counts became non-significant, while the association for rates became stronger, although the effect sizes were in a moderate (d = .28 or higher) to large range (d, up to .68) by either analysis. Generally, research quality acted as a suppressor variable for MLSD but was significantly related to both counts and rates of citations, indicating that higher quality articles were more likely to have been cited, even controlling for the number of years since first publication. Higher quality articles were slightly more likely to report higher rates of nonheterosexuality among children of same-sex parents. We discuss implications of our findings and suggest future directions of research.

Developmental Mathematics: Students’ Predicted Outcome Value of Electronic Communication

This study investigated the predicted outcome value of electronic communication from the viewpoint of developmental mathematics students. Students at a large Texas community college completed a combination of instruments that were administered in three prior studies. Three reasons for using electronic communication that were included in this study were procedural/clarification, personal/social, and efficiency. Results indicated that (a) student-initiated electronic communications conversations were correlated with students’ predicted outcome value of electronic communications; (b) instructor immediacy behaviors via electronic measures was correlated with students’ reasons for electronic communication; (c) instructor immediacy of electronic communication and the reasons for communicating explained 34.3% of the variance in students’ predicted outcome value of electronic communication; (d) procedural/clarification reasons was the largest predictor of predicted outcome value; and (e) the β weight and structure coefficient suggested that personal/social reasons was a possible suppressor. Keywords: developmental mathematics, electronic communication, predicted outcome value, regression, suppressor variable

Achieving More With Less: Intuitive Correction in Selection

Choosing between candidates for a position can be tricky, especially when the selection test is affected by irrelevant characteristics (e.g., reading speed). One can correct for this irrelevant attribute by penalizing individuals who have unjustifiably benefited from it. Statistical models do so by including the irrelevant attribute as a suppressor variable, but can people do the same without the help of a model? In three experiments (total N = 357), participants had to choose between two candidates, one of whom had higher levels of an irrelevant attribute and thus enjoyed an unfair advantage. Participants showed a substantial preference for the candidate with high levels of the irrelevant attribute, thus choosing the less suitable candidate. This bias was attenuated when the irrelevant attribute was a situational factor, probably by making the correction process more intuitive. Understanding the intuitive judgment of suppressor variables can help candidates from underprivileged groups boost their chances to succeed.

The Antagonistic Dark Core

The dark core represents the commonalities across the dark triad (Machiavellianism, Narcissism, and Psychopathy). This study contributes to the dark core literature by examining Antagonism as the prime member accounting for the dark core and tests its relative ability in explaining the dark core as compared to other such factors namely, Primary Psychopathy, Honesty-Humility and Agreeableness. A pool of 270 prospective managers (157 males, 113 females, Mage = 25.7 yrs., SDage = 3.2 years) from a leading business school of India were selected for this study. The obtained data was subjected to Hierarchical Linear Regression, Relative Weights Analysis and Commonality Analysis in a bid to flesh out unique and common variance attributed to each predictor for comparing the ability of Antagonism in explaining the dark core in relation to other variables. Antagonism was found to outperform other predictors in accounting for the dark core and explaining variance associated with Narcissism. Honesty-Humility was found to be acting as a suppressor variable, thus increasing the predictive ability of Antagonism and Primary Psychopathy in accounting for the dark core. In short, dark traited people are antagonistic at core.

How a variable’s partial correlation with other variable(s) can make a good predictor: the suppressor variable case

<p>Suppression effect is one of the most elusive and difficult to understand dynamics in multiple regression analysis. Suppressor variable(s) and their dynamics in multiple regression analyses are important in reporting accurate research outcomes. However, quite a number of researchers are unfamiliar with the possible advantages and importance of these variables. Suppressor variables tend to appear useless as separate predictors, but have the potential to change the predictive ability of other variables and completely influence research outcomes. This research describes the role suppressor variables play in a multiple regression analysis and provides practical examples that further explain how suppressor effects can alter research outcomes. Finally, we employed mathematical set notation to demonstrate the concepts of suppressor effects.</p>