Biomedical subjects

Niels G Waller

Publications and source records attributed to Niels G Waller.

4 recordsLinked to original sources

PubMed2004

Enhancing power while controlling family-wise error: an illustration of the issues using electrocortical studies.

This study examined the relative family-wise error (FWE) rate and statistical power of multivariate permutation tests (MPTs), Bonferroni-adjusted alpha, and uncorrected-alpha tests of significance for bivariate associations. Although there are many previous applications of MPTs, this is the first to apply it to testing bivariate associations. Electrocortical studies were selected as an example class because the sample sizes that are typical of electrocortical studies published in 2001 and 2002 are small and their multiple significance tests are typically nonindependent. Because Bonferroni adjustments assume independent predictors, we expected that MPTs would be more powerful than the Bonferroni adjustment. Results support the following conclusions: (a) failure to control for multiple significance testing results in unacceptable FWE rates, (b) the FWE rate for the MPTs approximated the alpha set for the analyses, and (c) the statistical power advantage that MPTs provide over Bonferroni adjustments is important when using small sample sizes such as those that are typical of recent electrocortical studies.

Analysis of Variance↗

PubMed2003

Potential problems with "well fitting" models.

The assessment of model fit is a more complex and indeterminate process than is commonly acknowledged by researchers who use structural equation modeling (SEM) techniques. Even models that are well fitting according to commonly used statistical tests and descriptive fit indices can have significant problems and ambiguities. The authors discuss 7 potential difficulties that can arise and that should temper researchers' conclusions: equivalent models, nonequivalent but well-fitting alternative models, omitted variables, problematic lower-order model components, the failure to parse composite models into meaningful partitions (e.g., measurement vs. structural), inattention to the multiple factors that affect the sensitivity of measures of fit to model misspecifications, and reliance on specification searches. In addition to providing examples of each of these problems, the authors offer recommendations for psychopathologists who conduct SEM analyses.

Analysis of Variance↗

PubMed2003

How many IRT parameters does it take to model psychopathology items?

The authors compared the fit of the 2- and 3-parameter logistic models (2PLM; 3PLM) on 15 unidimensional factor scales derived from the Minnesota Multiphasic Personality Inventory--Adolescent item pool. Log-likelihood chi-square deviance tests indicated that a 3PLM provided an improved fit. However, residual statistics indicated that the difference in fit between the 2 models was negligible. An unexpected finding was that from 10% to 30% of the items had substantial lower asymptote parameters (c > or = .10) when the scales were scored in the pathology or nonpathology directions. The authors argue that the large lower asymptote parameters are attributable to item-content ambiguity possibly caused by item-level multidimensionality. These findings suggest that the direction of scoring can critically affect an item response theory analysis.

Adolescent↗

PubMed2002

The path analysis controversy: a new statistical approach to strong appraisal of verisimilitude.

A new approach for using path analysis to appraise the verisimilitude of theories is described. Rather than trying to test a model's truth (correctness), this method corroborates a class of path diagrams by determining how well they predict intradata relations in comparison with other diagrams. The observed correlation matrix is partitioned into disjoint sets. One set is used to estimate the model parameters, and a nonoverlapping set is used to assess the model's verisimilitude. Computer code was written to generate competing models and to test the conjectured model's superiority (relative to the generated set) using diagram combinatorics and is available on the Web (http://www.vanderbilt.edu/quantmetheval/downloads.htm).

Humans↗