Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.

Background: In health economic evaluations, model parameters are often dependent on other model parameters. Although methods exist to simulate multivariate normal (MVN) distribution data and estimate transition probabilities in Markov models while considering competing risks, they are technically challenging for health economic modellers to implement. This tutorial introduces easily implementable applications for handling dependent parameters in modelling.

Evaluating the correlations of cost and utility parameters from summary statistics for probabilistic analysis in economic evaluations.

Objectives: The correlations between economic modeling input parameters directly impact the variance and may impact the expected values of model outputs. However, correlation coefficients are not often reported in the literature. We aim to understand the correlations between model inputs for probabilistic analysis from summary statistics.

Age Differences in Thermal Pain Responses: A Direct Laboratory Comparison.

Objectives: According to a widely cited assertion, older adults are less likely than younger individuals to express pain complaints. Age-related differences in pain responses have been discussed in the literature despite a paucity of research involving direct comparisons of younger and older adults' pain reactions (i.e.

Understanding bias in probabilistic analysis in model-based health economic evaluation.

Guidelines of economic evaluations suggest that probabilistic analysis (using probability distributions as inputs) provides less biased estimates than deterministic analysis (using point estimates) owing to the non-linear relationship of model inputs and model outputs. However, other factors can also impact the magnitude of bias for model results. We evaluate bias in probabilistic analysis and deterministic analysis through three simulation studies.

Examining the correlation between treatment effects in clinical trials and economic modeling.

Introduction: Many diseases have a sequential treatment pathway. Compared with patients without previous treatment, patients who fail initial treatment may have lower success rates with a second treatment. This phenomenon can be explained by a correlation between treatment effects.

Logarithmic confidence estimation of a ratio of binomial proportions for dependent populations.

This article investigates the logarithmic interval estimation of a ratio of two binomial proportions in dependent samples. Previous studies suggest that the confidence intervals of the difference between two correlated proportions and their ratio typically do not possess closed-form solutions. Moreover, the computation process is complex and often based on a maximum likelihood estimator, which is a biased estimator of the ratio.

Review and estimation of disutility for joint health states of severe and nonsevere hypoglycemic events in diabetes.

Many economic evaluations used linear or log-transformed additive methods to estimate the disutility of hypoglycemic events in diabetes, both nonsevere (NSHEs) and severe (SHEs). We conducted a literature search for studies of disutility for hypoglycemia. We used additive, minimum and multiplicative methods, and the adjusted decrement estimator to estimate the disutilities of joint health states with both NSHEs and SHEs in six scenarios.

Comparison of the expected rewards between probabilistic and deterministic analyses in a Markov model.

: In Markov models that evaluate the cost-effectiveness of health-care technologies, it is generally recommended to use probabilistic analysis instead of deterministic analysis. We sought to compare the performance of probabilistic and deterministic analysis in estimating the expected rewards in a Markov model.: We applied Jensen's inequality to compare the expected Markov rewards between probabilistic and deterministic analysis and conducted a simulation study to compare the bias and accuracy between the two approaches.