Serious problems with the Mexican norms for the WAIS-III when assessing mental retardation in capital cases.

A Spanish-language translation of the Wechsler Adult Intelligence Scale-III (WAIS-III), normed in Mexico, is sometimes used when evaluating Spanish-speaking defendants in capital cases in order to diagnose possible mental retardation (MR). Although the manual for the Mexican test suggests use of the U.S. norms when diagnosing MR, the Mexican norms-which produce full-scale scores on average 12 points higher-are sometimes used for reasons that are similar to those used by proponents for "race-norming" in special education. Such an argument assumes, however, that the Mexican WAIS-III norms are valid. In this paper, we examined the validity of the Mexican WAIS-III norms and found six very serious problems with those norms: (1) extremely poor reliability, (2) lack of a meaningful reference population, (3) lack of score normalization, (4) exclusion of certain groups from the standardization sample, (5) use of incorrect statistics and calculations, and (6) incorrect application of the true score confidence interval method. An additional problem is the apparent absence of any social policy consensus within Mexico as to the definition and boundary parameters of MR. Taken together, these concerns lead one to the inescapable conclusion that the Mexican WAIS-III norms are not interpretable and should not be used for any high-stakes purpose, especially one as serious as whether a defendant should qualify for exemption against imposition of the death penalty.

Reply to Sanchez Escobedo and Hollingworth: Why the Mexican Norms for the WAIS-III continue to be inadequate.

The discussion in Drs. Sanchez Escobedo and Hollingworth's paper independently confirms virtually all our observations regarding the psychometric and interpretive deficiencies of the Mexican norms for very high-stakes decisions, such as that involved in an Atkins hearing. Test publishers have an ethical obligation to caution potential users against the premature use of a developing assessment that does not yet meet the needed precision and evidence of validity required for very high-stakes decisions.

Empirical Bayes estimation of the prevalence of uninsured individuals by county in the state of Tennessee and analyses of predictive factors.

Lawmakers at the state level require good estimates of those without health insurance in the areas they serve to inform policy decisions. These estimates are often built on inadequate data from smaller geographic areas, such as counties. The Small Area Estimates Branch of the U.S. Census Bureau developed a method to generate stable estimates at the county level using data from the Annual Social and Economic Supplement to the Current Population Survey and several other sources. Using data collected in the state of Tennessee, this article presents a less complicated and arguably less expensive alternative to that method, while providing comparable results. Limitations of both methods and suggestions for future research are discussed.

Assessing the impact of the local environment on birth outcomes: a case for HLM.

Hierarchical linear Models (HLM) is a useful way to analyze the relationships between community level environmental data, individual risk factors, and birth outcomes. With HLM we can determine the effects of potentially remediable environmental conditions (e.g., air pollution) after controlling for individual characteristics such as health factors and socioeconomic factors. Methodological limitations of ecological studies of birth outcomes and a detailed analysis of the varying models that predict birth weight will be discussed. Ambient concentrations of criterion air pollutants (e.g., lead and sulfur dioxide) demonstrated a sizeable negative effect on birth weight; while the economic characteristics of the mother's residential census tract (ex. poverty level) also negatively influenced birth weight.