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Your search keyword '"Day, Nancy L."' showing total 29 results
Start Over Author "Day, Nancy L." Publisher wiley
29 results on '"Day, Nancy L."'

1. Benchmark dose profiles for bivariate exposures

Author

Akkaya Hocagil, Tugba, primary, Ryan, Louise M., additional, Cook, Richard J., additional, Dang, Khue‐Dung, additional, Carter, R. Colin, additional, Richardson, Gale A., additional, Day, Nancy L., additional, Coles, Claire D., additional, Carmichael Olson, Heather, additional, Jacobson, Sandra W., additional, and Jacobson, Joseph L., additional

Published
2024
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2. A hierarchical meta-analysis for settings involving multiple outcomes across multiple cohorts

Author

Hocagil, Tugba Akkaya, Ryan, Louise M., Cook, Richard J., Richardson, Gale A., Day, Nancy L., Coles, Claire D., Olson, Heather Carmichael, Jacobson, Sandra W., and Jacobson, Joseph L.

Subjects
Methodology (stat.ME), FOS: Computer and information sciences, 0104 Statistics, Statistics - Methodology
Abstract

Evidence from animal models and epidemiological studies has linked prenatal alcohol exposure (PAE) to a broad range of long-term cognitive and behavioral deficits. However, there is virtually no information in the scientific literature regarding the levels of PAE associated with an increased risk of clinically significant adverse effects. During the period from 1975-1993, several prospective longitudinal cohort studies were conducted in the U.S., in which maternal reports regarding alcohol use were obtained during pregnancy and the cognitive development of the offspring was assessed from early childhood through early adulthood. The sample sizes in these cohorts did not provide sufficient power to examine effects associated with different levels and patterns of PAE. To address this critical public health issue, we have developed a hierarchical meta-analysis to synthesize information regarding the effects of PAE on cognition, integrating data on multiple endpoints from six U.S. longitudinal cohort studies. Our approach involves estimating the dose-response coefficients for each endpoint and then pooling these correlated dose-response coefficients to obtain an estimated `global' effect of exposure on cognition. In the first stage, we use individual participant data to derive estimates of the effects of PAE by fitting regression models that adjust for potential confounding variables using propensity scores. The correlation matrix characterizing the dependence between the endpoint-specific dose-response coefficients estimated within each cohort is then run, while accommodating incomplete information on some endpoints. We also compare and discuss inferences based on the proposed approach to inferences based on a full multivariate analysis

Published
2022

4. Effects of prenatal alcohol exposure on cognitive and behavioral development: Findings from a hierarchical meta‐analysis of data from six prospective longitudinal U.S. cohorts

Author

Jacobson, Joseph L., primary, Akkaya‐Hocagil, Tugba, additional, Ryan, Louise M., additional, Dodge, Neil C., additional, Richardson, Gale A., additional, Olson, Heather Carmichael, additional, Coles, Claire D., additional, Day, Nancy L., additional, Cook, Richard J., additional, and Jacobson, Sandra W., additional

Published
2021
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29. A residuals-based transition model for longitudinal analysis with estimation in the presence of missing data.

Author

Koru-Sengul T, Stoffer DS, and Day NL

Subjects
Humans, Stochastic Processes, United States, Bias, Data Interpretation, Statistical, Longitudinal Studies
Abstract

We propose a transition model for analysing data from complex longitudinal studies. Because missing values are practically unavoidable in large longitudinal studies, we also present a two-stage imputation method for handling general patterns of missing values on both the outcome and the covariates by combining multiple imputation with stochastic regression imputation. Our model is a time-varying auto-regression on the past innovations (residuals), and it can be used in cases where general dynamics must be taken into account, and where the model selection is important. The entire estimation process was carried out using available procedures in statistical packages such as SAS and S-PLUS. To illustrate the viability of the proposed model and the two-stage imputation method, we analyse data collected in an epidemiological study that focused on various factors relating to childhood growth. Finally, we present a simulation study to investigate the behaviour of our two-stage imputation procedure.

Published
2007
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