Psychometric Properties of the Schizotypal Personality Questionnaire (SPQ) in a Mexican Population: Invariance Across Gender and Age.

BACKGROUND: The present study tested the factorial structure of the Schizotypal Personality Questionnaire (SPQ) in Mexican adults. Although this instrument has been validated in different cultural contexts, there are no studies to date that analyze its psychometric properties in a Mexican sample. METHOD: 307 adults completed the SPQ, seven participants were removed for being at high risk of psychosis. The final sample was made up of 300 participants (M = 34.58, SD = 13.77), of whom 62.8% were female. Raine's three-factor model and Stefanis et al.'s four-factor model were tested. RESULTS: The results indicated that both factor structures had a good fit to the data. However, the best evidence was for the three-factor solution. Configural, metric, and scalar invariance according to gender and age for the three-factor model was displayed. Further analyses showed women scored slightly higher in excessive social anxiety but this result was not statistically significant. Younger participants had higher scores on ideas of reference, excessive social anxiety, no close friends, and odd speech than the older group. CONCLUSIONS: These findings provide support for the use of the SPQ in the Mexican population.

False discovery rate and permutation test: an evaluation in ERP data analysis.

Current analysis of event-related potentials (ERP) data is usually based on the a priori selection of channels and time windows of interest for studying the differences between experimental conditions in the spatio-temporal domain. In this work we put forward a new strategy designed for situations when there is not a priori information about 'when' and 'where' these differences appear in the spatio-temporal domain, simultaneously testing numerous hypotheses, which increase the risk of false positives. This issue is known as the problem of multiple comparisons and has been managed with methods that control the false discovery rate (FDR), such as permutation test and FDR methods. Although the former has been previously applied, to our knowledge, the FDR methods have not been introduced in the ERP data analysis. Here we compare the performance (on simulated and real data) of permutation test and two FDR methods (Benjamini and Hochberg (BH) and local-fdr, by Efron). All these methods have been shown to be valid for dealing with the problem of multiple comparisons in the ERP analysis, avoiding the ad hoc selection of channels and/or time windows. FDR methods are a good alternative to the common and computationally more expensive permutation test. The BH method for independent tests gave the best overall performance regarding the balance between type I and type II errors. The local-fdr method is preferable for high dimensional (multichannel) problems where most of the tests conform to the empirical null hypothesis. Differences among the methods according to assumptions, null distributions and dimensionality of the problem are also discussed.