There is a simple robust variance estimator for cluster-correlated data. While this estimator is well known, it is poorly documented, and its wide range of applicability is often not understood. The estimator is widely used in sample survey research, but the results in the sample survey literature are not easily applied because of complications due to unequal probability sampling. This brief note presents a general proof that the estimator is unbiased for cluster-correlated data regardless of the setting. The result is not new, but a simple and general reference is not readily available. The use of the method will benefit from a general explanation of its wide applicability.

There is increasing interest in estimating and drawing inferences about risk or prevalence ratios and differences instead of odds ratios in the regression setting. Recent publications have shown how the GENMOD procedure in SAS (SAS Institute Inc., Cary, North Carolina) can be used to estimate these parameters in non-population-based studies. In this paper, the authors show how model-adjusted risks, risk differences, and risk ratio estimates can be obtained directly from logistic regression models in the complex sample survey setting to yield population-based inferences. Complex sample survey designs typically involve some combination of weighting, stratification, multistage sampling, clustering, and perhaps finite population adjustments. Point estimates of model-adjusted risks, risk differences, and risk ratios are obtained from average marginal predictions in the fitted logistic regression model. The model can contain both continuous and categorical covariates, as well as interaction terms. The authors use the SUDAAN software package (Research Triangle Institute, Research Triangle Park, North Carolina) to obtain point estimates, standard errors (via linearization or a replication method), confidence intervals, and P values for the parameters and contrasts of interest. Data from the 2006 National Health Interview Survey are used to illustrate these concepts.

Because most prescription ADHD medications currently are highly regulated, policy options for supply-side reduction of nonmedical use may include identifying those medications with lower abuse liability for inclusion on insurance formularies. Patient and physician education programs also may be useful tools to heighten awareness of intentional and unintentional diversion of ADHD medications for nonmedical purposes.

This paper demonstrates the use of the delta method for estimating the variance of ratio statistics derived from animal carcinogenicity experiments. The Cochran-Armitage test (Cochran, 1954, Biometrika 10, 417-451; and Armitage, 1955, Biometrics 11, 375-386) is routinely applied to carcinogenicity data as a test for linear trend in lifetime tumor incidence rates. The computing formula for this test derives from the assumption that the denominators of the quantal response rates are fixed. However, when time-at-risk weights are introduced to correct for treatment-related differences in survival, the denominators of the quantal response rates are subject to random variation. The delta method and weighted least squares techniques are applied here to approximate the variance of such ratio statistics and test for a linear dose-response relationship among treatments. This technique is compared to that of Bailer and Portier (1988, Biometrics 44, 417-431), who introduced a survival-adjusted quantal response test for trend in lifetime tumor incidence rates. Their test modifies the usual Cochran-Armitage computing formula by weighting the denominators of the response rates to reflect less-than-whole-animal contributions to risk. Within the framework of a weighted least squares linear regression model that underlies the Cochran-Armitage test, the time-at-risk weights of Bailer and Portier are incorporated using the delta method. Although the delta method approach is slightly more computationally intensive, small-sample simulations indicate that it has superior operating characteristics over the Poly-3 trend test of Bailer and Portier when background tumor incidence rates are low (under 3%) and survival patterns differ markedly across treatments.(ABSTRACT TRUNCATED AT 250 WORDS)

Recent reports indicate that breastfeeding rates continue to be dramatically lower among WIC participants, compared with other US mothers. The WIC Infant Feeding Practices Study was a nationally representative 1-year longitudinal study of WIC participants that obtained information about attitudes regarding infant feeding and about infant-feeding practices. Hispanic mothers were most likely to agree with statements about benefits of breastfeeding, and Black mothers were most likely to agree with statements about barriers. Concern about insufficient milk was common in all ethnic groups. Perceived benefits were associated with breastfeeding initiation (P < .05), longer breastfeeding duration (P < .01), and later formula initiation (P < .01); for barriers, the opposite pattern was found. Breastfeeding mothers who reported concern about insufficient milk breastfed for shorter durations (P < .001) and initiated formula earlier (P < .01). These results suggest possible messages that should be communicated as part of a re-energized WIC breastfeeding promotion campaign. In particular, maternal anxiety about insufficient breast milk must be addressed.