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The association between study design features and prevalence estimates.

Figshare2018-02-10 更新2026-04-29 收录

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资源简介：

The association between study design features and prevalence estimates.

应用场景：

创建时间：

2018-02-10

流行率估计

流行病学方法

Accurately estimating infection prevalence is fundamental to the study of population health, disease dynamics, and infection risk factors. Prevalence is estimated as the proportion of infected individ

NIAID Data Ecosystem80

Expected bias of effect estimates due to association of exposure and outcome variable with participation in a study (collider) under simplified assumptions.

因果推理偏差校正

流行病学方法

(XLSX)

NIAID Data Ecosystem40

Estimated type I error probability for test of deviation from HWP of SNP 2 , a causal SNP to primary disease but unassociated with secondary phenotype (MAF = 10%), at 0.05 and 0.0001 significance levels in simulation studies * using different approaches for HWP testing.

流行病学方法

Hardy-Weinberg平衡

*Simulation studies were based on 1,000,000 replicates, each replicate with 2,000 cases in terms of primary disease and 2,000 controls frequency-matched on secondary phenotype. MAF: minor allele frequ

NIAID Data Ecosystem40

SNP data: Comparison of molecular surveillance methods to assess changes in the population genetics of Plasmodium falciparum in high-transmission

疟疾寄生虫基因

流行病学方法

Genetic diversity and population structure of Plasmodium falciparum are assessed here using three established methods (i) SNP barcoding (panel of 24-biallelic loci), (ii) microsatellite genotyping (pa

NIAID Data Ecosystem60

Sources of selection bias in excluded patients.

临床试验偏倚

流行病学方法

Sources of selection bias in excluded patients.

Figshare2015-12-02 更新40