I get the impression that a lot of people around the web confound absolutely everything when talking about correlations on the topic of social sciences. They supply a biased, incomplete, or truncated reality of what actually really is.
Pui-Wa Lei and Qiong Wu, The Pennsylvania State University (Fall 2007)
Structural equation modeling (SEM) is a versatile statistical modeling tool. Its estimation techniques, modeling capacities, and breadth of applications are expanding rapidly. This module introduces some common terminologies. General steps of SEM are discussed along with important considerations in each step. Simple examples are provided to illustrate some of the ideas for beginners. In addition, several popular specialized SEM software programs are briefly discussed with regard to their features and availability. The intent of this module is to focus on foundational issues to inform readers of the potentials as well as the limitations of SEM. Interested readers are encouraged to consult additional references for advanced model types and more application examples.
In the present article, I demonstrate that processing speed (using ASVAB speeded subtests) has a modest predictive validity over the g factor extracted from the ASVAB (non-speeded subtests) in predicting overall GPA in the NLSY97, within black, hispanic and the white sample. Next, I investigate the mediation of speed in the black-white difference in IQ (g). For both analyses, processing speed accounts for a modest portion of these associations. Nonetheless, some issues related with such ‘psychometric speed’ measures need to be clarified.
Kevin M. Beaver, John Paul Wright (2011)
Research has consistently revealed that average IQ scores vary significantly across macro-level units, such as states and nations. The reason for this variation in IQ, however, has remained at the center of much controversy. One of the more provocative explanations is that IQ across macro-level units is the result of genetic differences, but empirical studies have yet to examine this possibility directly. The current study partially addresses this gap in the literature by examining whether average IQ scores across thirty-six schools are associated with differences in the allelic distributions of dopaminergic polymorphisms across schools. Analysis of data drawn from subjects (ages 12–19 years) participating in the National Longitudinal Study of Adolescent Health provides support in favor of this perspective, where variation in school-level IQ scores was predicted by school-level genetic variation. This association remained statistically significant even after controlling for the effects of race.
Kanazawa (2004) earlier demonstrated that children would not make the parents happier. Parenthood decreases happiness. Using the GSS data (available here) he was trying to see whether or not an interaction effect (parenthood*married) is substantial with which sign it has but also the impact of parenthood net of the effect of being married. Being married and the interaction term had a positive sign on happiness (dependent variable) while parenthood had a strong negative sign. Here, I will try to replicate that analysis with GSS data using logistic regression. After this, I will comment Myrskylä and Margolis (2012) study for which my conclusion differ from theirs.
A bad, invalid argument commonly used by hereditarians is the research concerning transracial adoption. The claim usually made is that black, black-white mixed-race, white, asian-white mixed-race adoptees had IQs following the well-established genetic hierarchy seemingly B < BW < W < AW.