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At least 667 records · Page 37Linked to original sources
PubMed1994

Nonparametric regression analysis of data from the Ames mutagenicity assay.

The Ames assay has received widespread attention from statisticians because of its popularity and importance to risk assessment. However, investigators have yet to routinely apply modern regression methods that have been available for more than a decade. We study yet another approach, the application of nonparametric regression techniques, not as the ultimate solution but rather as a framework within which to address some of the shortcomings of other methods. But nonparametric regression is itself prone to difficulties when applied to Ames assay data, as we show through the use of two examples and some simulation studies. We argue that there remains a great need for further development of statistical methods suitable to the Ames assay. It is hoped that such work can be stimulated and guided by greater collaboration between statisticians and laboratory investigators.

Bias↗
PubMed1989

Logistic regression analysis of risk factors for intra-amniotic infection.

The identification of risk factors for intra-amniotic infection may allow changes in obstetric management and reduce complications. In a pilot study, stepwise logistic regression identified duration of ruptured membranes and duration of interval monitoring as significant risk factors for intra-amniotic infection. Using the preliminary regression equation, we established critical durations (risk criteria) to predict a 20% or greater probability of intra-amniotic infection. Subsequently, 2908 patients were screened prospectively for risk criteria and/or the presence of intra-amniotic infection. Seven hundred five patients of the 2908 (24%) met the risk criteria, and 107 of 124 cases of intra-amniotic infection (86%) met the risk criteria. In patients meeting the risk criteria, the relative risk of intra-amniotic infection was 19.7. In addition, 81 of 705 (12%) of mothers developed endometritis. Ten neonates of mothers with criteria developed sepsis or pneumonia. A stepwise logistic regression performed on the prospectively gathered data showed that among patients meeting risk criteria, parity, duration of internal monitoring, and duration of membrane rupture were the significant risk factors for intra-amniotic infection.

Adult↗
PubMed2005

Exploring the equity of GP practice prescribing rates for selected coronary heart disease drugs: a multiple regression analysis with proxies of healthcare need.

BACKGROUND: There is a small, but growing body of literature highlighting inequities in GP practice prescribing rates for many drug therapies. The aim of this paper is to further explore the equity of prescribing for five major CHD drug groups and to explain the amount of variation in GP practice prescribing rates that can be explained by a range of healthcare needs indicators (HCNIs). METHODS: The study involved a cross-sectional secondary analysis in four primary care trusts (PCTs 1-4) in the North West of England, including 132 GP practices. Prescribing rates (average daily quantities per registered patient aged over 35 years) and HCNIs were developed for all GP practices. Analysis was undertaken using multiple linear regression. RESULTS: Between 22-25% of the variation in prescribing rates for statins, beta-blockers and bendrofluazide was explained in the multiple regression models. Slightly more variation was explained for ACE inhibitors (31.6%) and considerably more for aspirin (51.2%). Prescribing rates were positively associated with CHD hospital diagnoses and procedures for all drug groups other than ACE inhibitors. The proportion of patients aged 55-74 years was positively related to all prescribing rates other than aspirin, where they were positively related to the proportion of patients aged >75 years. However, prescribing rates for statins and ACE inhibitors were negatively associated with the proportion of patients aged >75 years in addition to the proportion of patients from minority ethnic groups. Prescribing rates for aspirin, bendrofluazide and all CHD drugs combined were negatively associated with deprivation. CONCLUSION: Although around 25-50% of the variation in prescribing rates was explained by HCNIs, this varied markedly between PCTs and drug groups. Prescribing rates were generally characterised by both positive and negative associations with HCNIs, suggesting possible inequities in prescribing rates on the basis of ethnicity, deprivation and the proportion of patients aged over 75 years (for statins and ACE inhibitors, but not for aspirin).

Journal Article↗
PubMed2000

Alcohol abuse and crime: a fixed-effects regression analysis.

AIMS: To examine linkages between patterns of alcohol abuse and crime in a New Zealand birth cohort studied to the age of 21 taking into account confounding factors through the use of fixed-effects regression methods. MEASUREMENTS: Over the period from age 15-21 years assessments were made of: (a) involvement in violent and property crime; and (b) extent (if any) of alcohol abuse/dependence symptoms. In addition, information was gathered on a number of social and contextual factors that were likely to be related to alcohol abuse or crime. FINDINGS: Increasing alcohol abuse was associated with clear and significant (p < 0.0001) increases in rates of both violent and property crime. Control for observed and non-observed confounding through the use of fixed-effects regression models indicated that much of this association was attributable to the effects of confounding factors that were associated with both alcohol abuse and crime. None the less, even after such control alcohol abuse remained significantly related to both violent and property offending. CONCLUSIONS: The findings suggest the presence of a possible causal association between alcohol abuse and juvenile offending that is evident after control for both observed and non observed sources of confounding.

Adolescent↗
PubMed2005

Identification of genes required for cellulose synthesis by regression analysis of public microarray data sets.

Coexpression patterns of gene expression across many microarray data sets may reveal networks of genes involved in linked processes. To identify factors involved in cellulose biosynthesis, we used a regression method to analyze 408 publicly available Affymetrix Arabidopsis microarrays. Expression of genes previously implicated in cellulose synthesis, as well as several uncharacterized genes, was highly coregulated with expression of cellulose synthase (CESA) genes. Four candidate genes, which were coexpressed with CESA genes implicated in secondary cell wall synthesis, were investigated by mutant analysis. Two mutants exhibited irregular xylem phenotypes similar to those observed in mutants with defects in secondary cellulose synthesis and were designated irx8 and irx13. Thus, the general approach developed here is useful for identification of elements of multicomponent processes.

Arabidopsis↗
PubMedDate not supplied

Regression analysis with clustered data.

Clustered data are found in many different types of studies, for example, studies involving repeated measures, inter-rater agreement studies, household surveys, crossover designs and community randomized trials. Analyses based on population average and cluster specific models are commonly used for estimating treatment (exposure) effects with clustered data. This paper discusses conditions when one or both types of models are appropriate for estimating causal effects and when there is agreement between population average and cluster specific analyses. Applications of survey sampling methods to the robust estimation of standard errors of estimated treatment parameters are discussed.

Animals↗
PubMed2001

Joint regression analysis of survival and quality-adjusted survival.

In this paper, a semiparametric bivariate linear regression model for survival and quality-adjusted survival is investigated. Even with a parametric specification for the joint, distribution, maximum likelihood is not applicable because of induced informative censoring. We propose inference procedures based on estimating functions. The estimators are consistent and asymptotically normal. Hypothesis tests and confidence intervals may be constructed with easy-to-implement resampling techniques. Simultaneous regression modeling of survival and quality-adjusted survival has not been studied formally. Our methodology gives parameter estimates that are highly interpretable in the context of a cost-effectiveness analysis. The usefulness of the proposal is illustrated with a breast cancer dataset.

Age Factors↗