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On the Specification of Likelihood Functions for Matched Case-Control Designs: Implications for Resource Selection Studies

Citation

Ng, Elizabeth Laurel. (2016). On the Specification of Likelihood Functions for Matched Case-Control Designs: Implications for Resource Selection Studies. Theses and Dissertations Collection, University of Idaho Library Digital Collections. https://www.lib.uidaho.edu/digital/etd/items/ng_idaho_0089n_10964.html

Title:
On the Specification of Likelihood Functions for Matched Case-Control Designs: Implications for Resource Selection Studies
Author:
Ng, Elizabeth Laurel
Date:
2016
Keywords:
conditional logistic regression matched case-control design mixed-effects logistic regression resource selection
Program:
Statistical Sciences
Subject Category:
Statistics; Natural resource management
Abstract:

Matched case-control designs are used in ecology and wildlife management to estimate resource selection functions, which provide insight into habitat use by animals. Recent suggestions to incorporate random effects into these models have little statistical justification because they incorrectly assume unconstrained sampling of study sites, ignoring matching in the study design. Matched case-control designs have been used extensively in epidemiology, where conditional likelihood functions are used to account for constrained sampling. Here, we illustrate the discrepancies between the constrained and unconstrained models, and evaluate the bias of parameter estimates using simulation. We evaluated the conditional logistic model, which produces consistent estimates, and compared results with estimates from prospective logistic models, stratified case-control models, and marginal logistic models. Conditional logistic models had the lowest bias across a wide range of sampling schemes and parameter values. In contrast, marginal logistic models tended to have greater bias and poor confidence interval coverage rates.

Description:
masters, M.S., Statistical Sciences -- University of Idaho - College of Graduate Studies, 2016
Major Professor:
Johnson, Timothy R
Committee:
Buzbas, Erkan O; Long, Ryan A
Defense Date:
2016
Identifier:
Ng_idaho_0089N_10964
Type:
Text
Format Original:
PDF
Format:
application/pdf

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