Quantifying and reducing statistical uncertainty in sample-based health program costing studies in low- and middle-income countries.

ABSTRACT:

Objectives

In many low- and middle-income countries, the costs of delivering public health programs such as for HIV/AIDS, nutrition, and immunization are not routinely tracked. A number of recent studies have sought to estimate program costs on the basis of detailed information collected on a subsample of facilities. While unbiased estimates can be obtained via accurate measurement and appropriate analyses, they are subject to statistical uncertainty. Quantification of this uncertainty, for example, via standard errors and/or 95% confidence intervals, provides important contextual information for decision-makers and for the design of future costing studies. While other forms of uncertainty, such as that due to model misspecification, are considered and can be investigated through s

SUBMITTER: Rivera-Rodriguez CL 

PROVIDER: S-EPMC5888835 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature