A case study approach to estimating the burden of research misconduct in publicly funded medical research

The economic impact of research misconduct in medical research has been unexplored. While research misconduct in publicly funded medical research has increasingly been the object of discussion, public policy debate, government and institutional action, and scientific research, the costs of research misconduct have been unexamined. The author develops a model to estimate the per case cost of research misconduct, specifically the costs of fabrication, falsification, and plagiarism, in publicly funded medical research. Using the database of Research Misconduct Findings maintained by the Office of Research Integrity, Department of Health and Human Services, the model is used to estimate costs of research misconduct in public funded medical research among faculty during the period 2000-2005.^

Rules to limit snacking in front of the TV and childhood BMI status: Findings from the "Fun Families Study"

Childhood obesity is increasing at epidemic rates, and thus there is a need to target appropriate childhood behaviors that contribute to obesity. Many factors contribute to childhood weight status. The aim of this study was to look at relationships between parental rules to limit snacking while watching television and childhood weight status. The study looked at the presence of the behavior of snacking while watching television yesterday, congruence between child- and parent-reported perception of the presence of rules to limit snacking while watching television, and parent-reported frequency of children following rules to limit snacking while watching television. The outcomes were examined in a multi-ethnic population of children ages 6 to 9 years in Southeast Texas.^ This study was a cross-sectional secondary data analysis of the pilot program, Fun Families. This study examined baseline data from 202 parent-child dyads, which included both the control ( N= 101) and intervention groups (N= 101). Data were gathered using validated questions that were administered to 6-9 year old children and their primary caregiver (referred to as parent in the rest of the discussion) in Southeast Texas, between 2006 and 2008. The main study outcome was childhood weight status based on CDC BMI-for-age categories. The independent variables are (1) the presence of parental rules to limit snacking while watching television, (2) the congruence between child and parent about the presence of rules to limit snacking while watching television, and (3) the parent-reported frequency of the child following the rules to limit snacking while watching television. Chi-Square analyses were used to determine if weight status was different for (1) children who reported rules to limit snacking yesterday, (2) children who reported snacking, (3) children whose parents reported rules were present, and (4) those who had rule congruence with the parents not. Chi-Square analyses also examined if there was a difference in the presence of snacking behavior for children who reported rules, for children whose parents reported rules, and for those children who had congruence about rules. Linear regressions were used to determine if any of the studied variables predicted increased weight status or reported snacking while watching television yesterday.^ This study found that child-reported snacking yesterday was significantly different for children who reported rules (4.12, p= 0.04). Child-reported rules was significantly associated with (p= -0.14, α= 0.04) and predicted child-reported snacking yesterday (R 2 0.021, p= 0.04, t= -2.04, 95% CI -0.31, -0.01). There was statistical significant incongruence between child and parent perception about the presence of rules to limit snacking yesterday (15.06, p= 0.00). For this population, parent education level was significantly associated with child-reported rules (r= -0.16, p= 0.02), child-reported snacking yesterday (r= -0.15, p= 0.04), and parent-reported frequency of child following rules to limit snacking (r= 0.29, p= -0.01). Parent-reported speaking another language besides English at home was significantly associated with parent-reported rules (r= 0.17, p= 0.02).^ Although the studied variables did not show any significant associations or predictors for childhood weight status, the significant discord between parent and child perception about the presence of rules provides valuable information to future interventions that aim to reduce childhood weight status. Including the creation and enforcement of parental rules in interventions to reduce childhood weight status will be beneficial for future studies.^

A Bayesian approach to estimating the intraclass correlation coefficient

A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

A Bayesian approach to estimating the regression coefficients of a multinomial logit model

A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^