Module 15. Data processing and analysis

Data processing

Analyses for surveys designed with stratification and clustering

Additional information for interpreting nutrition indicators

Standard analysis and checks for anthropometry data

Introduction

Because this micronutrient survey manual focuses on the standard micronutrient survey design (a multi-stage cluster survey with or without stratification), this module focuses on processing and analysing data from surveys with this design. In specific situations, such as a survey in a refugee camp, where the simple random sampling (SRS) method is selected, analysis should be conducted using SRS-specific procedures. This usually means that there is no need to apply survey weights or a stratum or cluster variable when running frequency tables and generating mean estimates.

Analyses of micronutrient survey data should be conducted using software that accounts for multi-stage complex survey design with stratification. Such software includes Epi Info , SAS version 8.0 or later, SPSS with the optional SPSS Complex Samples module, Stata, Sudaan, and R.

Anthropometric indices and exclusion flags

Document explaining how to calculate anthropometric indices and which exclusion flags to use

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Calculating anthropometry Z-scores igrowup SAS

SAS code to calculate Z-scores

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Graph to plot anthropometric indices against reference population

Graph template that can be used to plot anthropometric indices against a reference population

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Sample weights

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Example data dictionary

Example data dictionary that can be used as a reference when building a survey specific dictionary

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R code - BRINDA: Computation of BRINDA Adjusted Micronutrient Biomarkers for Inflammation

The BRINDA R package is a user-friendly all-in-one R package that uses a series of functions to implement BRINDA adjustment method.

Details and R package are located here: https://cran.r-project.org/web/packages/BRINDA/index.html

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