.png){kind=icon}
返回
A Sample Size Formula for Network Scale-up Studies
.png){kind=icon}
PRE
AI
DOI：10.1177/00491241221122576.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The network scale-up method (NSUM) is a survey-based method for estimating the number of individuals in a hidden or hard-to-reach subgroup of a general population. In NSUM surveys, sampled individuals report how many others they know in the subpopulation of interest (e.g. How many sex workers do you know?) and how many others they know in subpopulations of the general population (e.g. How many bus drivers do you know?). NSUM is widely used to estimate the size of important sociological and epidemiological risk groups, including men who have sex with men, sex workers, HIV+ individuals, and drug users. Unlike several other methods for population size estimation, NSUM requires only a single random sample and the estimator has a conveniently simple form. Despite its popularity, there are no published guidelines for the minimum sample size calculation to achieve a desired statistical precision. Here, we provide a sample size formula that can be employed in any NSUM survey. We show analytically and by simulation that the sample size controls error at the nominal rate and is robust to some forms of network model mis-specification. We apply this methodology to study the minimum sample size and relative error properties of several published NSUM surveys.
Keyword:
network scale-up method
study design
sample size
relative error
hidden population
期刊
S
IF:
6.5
论文数:
1.2K
被引数:
8.6K
机构
引用论文
<p align="left">A new species of Postia (Polyporales, Basidiomycota) from China based on morphological and molecular evidence.png)
Phytotaxa
PhytotaxaIF0
PREAI
分享收藏Diet of dominant frugivorous bat species in an oil palm landscape from Colombian Llanos: implications for forest conservation and recoveryTherya
OAAI
TheryaIF0
OAAI分享收藏分享收藏
查看更多内容