Looking for homogeneous groups of respondents and nonrespondents using latent class analysis.

Concerns about decreasing response rates have led to many nonresponse studies. Unfortunately, usually only a limited amount of data is available on nonrespondents. Linking administrative data makes information available on all the sampled units including nonrespondents. Statistics Netherlands has constructed a database in which several administrative records and several surveys are connected. In this explorative study we use this dataset to look for homogenous groups of respondents and nonrespondents in survey research using latent class cluster analysis. Latent class techniques can provide insight into the problem of selective nonresponse and currently under-represented societal groups. We identify four different latent classes in a recent Dutch survey and replicate the findings for the same survey conducted 4 years later. Two of the types of sampled units have above-average response rates and the other two have below-average response rates. We also evaluate various latent class models with other response outcomes to gain insight into the contact and cooperation process.

Minor physical anomalies in autism: a meta-analysis.

Autism is a complex neurodevelopmental disorder in which the interactions of genetic, epigenetic and environmental influences play a causal role. Despite the compelling evidence for a strong heritability, the etiology and molecular mechanisms underlying autism remain unclear. High phenotypic variability and genetic heterogeneity confounds the identification of susceptibility genes. The lack of robust indicators to tackle this complexity in autism has led researchers to seek for novel diagnostic tools to create homogenous subgroups. Several studies have indicated that patients with autism have higher rates of minor physical anomalies (MPAs) and that MPAs may serve as a diagnostic tool; however, the results have been inconsistent. Using the cumulative data from seven studies on MPAs in autism, this meta-analysis seeks to examine whether the aggregate data provide evidence of a large mean effect size and statistical significance for MPAs in autism. It covers the studies using multiple research methods till June 2007. The current results from seven studies suggested a significant association of MPAs in autism with a robust pooled effect size (d=0.84), and thereby provide the strongest evidence to date about the close association between MPAs and autism. Our results emphasize the importance of MPAs in the identification of heterogeneity in autism and suggest that the success of future autism genetics research will be exploited by the use of MPAs. Implications for the design of future studies on MPAs in autism are discussed and suggestions for further investigation of these important markers are proposed. Clarifying this relation might improve understanding of risk factors and molecular mechanisms in autism.

DSM-IV internal construct validity: when a taxonomy meets data.

The use of DSM-IV based questionnaires in child psychopathology is on the increase. The internal construct validity of a DSM-IV based model of ADHD, CD, ODD, Generalised Anxiety, and Depression was investigated in 11 samples by confirmatory factor analysis. The factorial structure of these syndrome dimensions was supported by the data. However, the model did not meet absolute standards of good model fit. Two sources of error are discussed in detail: multidimensionality of syndrome scales, and the presence of many symptoms that are diagnostically ambiguous with regard to the targeted syndrome dimension. It is argued that measurement precision may be increased by more careful operationalisation of the symptoms in the questionnaire. Additional approaches towards improved conceptualisation of DSM-IV are briefly discussed. A sharper DSM-IV model may improve the accuracy of inferences based on scale scores and provide more precise research findings with regard to relations with variables external to the taxonomy.

Syndrome dimensions of the child behavior checklist and the teacher report form: a critical empirical evaluation.

The construct representation of the cross-informant model of the Child Behavior Checklist (CBCL) and the Teacher Report Form (TRF) was evaluated using confirmatory factor analysis. Samples were collected in seven different countries. The results are based on 13,226 parent ratings and 8893 teacher ratings. The adequacy of fit for the cross-informant model was established on the basis of three approaches: conventional rules of fit, simulation, and comparison with other models. The results indicated that the cross-informant model fits these data poorly. These results were consistent across countries, informants, and both clinical and population samples. Since inadequate empirical support for the cross-informant syndromes and their differentiation was found, the construct validity of these syndrome dimensions is questioned.