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Learn MoreStata for NFHS-India Data Analysis | DHS data analysis
Rating: 4.6 out of 54.6(28 ratings)
966 students
Stata for NFHS-India Data Analysis | DHS data analysis
NFHS-India data analysis in Stata: data management, descriptive analysis, regression, and research workflow
Created byMd Ahshanul Haque
Last updated 4/2026
English
What you'll learn
- Performing descriptive statistics and summary tables
- Running common statistical tests in Stata
- Creating clear graphs and charts for reports
- Practical tips for using Stata in Master’s and PhD research
Course content
9 sections • 58 lectures • 4h 9m total length
- Welcome to Stata: A Beginner’s Guide to Data Analysis2:19
Start your journey with Stata!
This beginner-friendly course will teach you how to analyze data in public health, social science, and market research. Learn step-by-step, practice hands-on, and gain confidence in using Stata for real-world data analysis.
- Start you Stata Journey2:54
Welcome to the first step of your Stata journey! This video is designed for absolute beginners and provides a gentle, step-by-step introduction to the Stata interface and essential concepts. You'll learn how to open and save files, navigate the command and results windows, and run your first few commands. By the end of this video, you'll feel comfortable and confident enough to start exploring your own data
- Stata on Windows / Interface3:10
This course is designed for anyone new to Stata, providing a comprehensive guide to using the software on a Windows operating system. You will learn how to navigate Stata's user-friendly interface, import and manage data, and perform fundamental statistical analyses. By the end of this course, you will be proficient in using Stata's powerful tools to prepare, analyze, and visualize your data with confidence
- Stata Clear Command, and clear the result and history2:20
This video demystifies one of Stata's most essential commands: clear. You'll learn exactly what clear does and, more importantly, when to use it to avoid errors and ensure your analyses are reproducible. We'll explore the difference between clear and clear all and demonstrate how these commands are the critical first step in every well-structured do-file. Master this command to keep your Stata sessions clean and your workflows efficient
- Understanding Stata Data Types: Numeric, String, and Dates5:05
Mastering data types is the first step to becoming a confident Stata user. In this video, we'll break down the different ways Stata stores data—numeric (byte, int, long, float, double), string (str1, strL), and date formats.
- Stata Do-File Explained: Write & Run Your First Script9:47
Move beyond the command window and start writing your own Stata scripts! This video provides a practical, step-by-step guide to using the do-file editor. You'll learn how to write, edit, and execute a series of commands in a single script, saving you time and preventing errors. We'll also cover crucial commands for managing your working directory and ensuring your code runs perfectly every time
- A Guide to Log Files | Never Lose Your Stata Output Again6:52
Tired of losing your results after every Stata session? This video provides a simple, foolproof method to save all your commands and output using Stata's powerful log files. We'll walk you through the key commands to automate this process, making it a seamless part of your workflow. By the end of this video, you'll have the confidence to keep a perfect, permanent record of all your Stata analyses.
- Arithmetic in Stata: The Essential Operators You Need to Know4:51
Struggling with calculations in Stata? This video breaks down the essential arithmetic operators you'll need for any data analysis project. We'll show you how to use +, -, *, and / to transform variables and compute new values quickly and accurately. This is a must-watch for anyone who needs to perform simple math on their data, whether it's calculating a new total, a difference, or a ratio. Master these operators to make your data manipulation workflow much smoother.
- Logical Operators in Stata9:11
This video is your complete guide to using logical operators in Stata. You'll learn how to combine conditions and create complex selection criteria using operators like AND (&), OR (|), and NOT (!). We will show you how to apply these operators in powerful commands like if and gen to precisely select or modify subsets of your data. By the end of this video, you will be able to write sophisticated and efficient code for conditional data manipulation.
- How to Use label Commands to Show Values and Labels2:55
Value labels in Stata are a great way to make your data more readable. For example, instead of seeing a variable with values "1" and "2," you can attach a value label so it displays as "Male" and "Female."
- Data management part - 11:17
Duplicate ID check and Duplicates drop
Stata Data Sorting: Ascending vs. Descending Order
Stata Variable Order: Using order command to Organize Your Data
Stata: How to drop and keep Variables
Stata: How to drop and keep Cases
Rename Variable in Stata
Missing value in Stata
- Duplicate ID check and Duplicates drop3:29
Duplicate data can ruin your analysis. This video provides a step-by-step guide to finding and removing duplicate observations in Stata. You'll learn how to use the duplicates command to identify duplicate IDs, list the full observations, and efficiently drop them from your dataset. Master this essential data cleaning skill to ensure your analysis is accurate and reliable.
- Stata Data Sorting: Ascending vs. Descending Order3:18
Learn to organize your data with precision. This video explains the fundamental difference between sorting in ascending and descending order. We'll cover the essential sort command for basic ascending order and the more powerful gsort command for sorting in any direction. By the end, you'll be able to quickly arrange your data for any task, from cleaning to merging.
- Stata Variable Order: Organizing Your Data with the order Command3:42
A well-organized dataset is easier to work with. This video is a practical guide to using the order command to rearrange your variables. You'll learn how to move specific variables to the beginning, place them next to related variables, or simply sort them alphabetically. This simple but powerful skill will make your data view and analysis much cleaner and more efficient
- How to drop and keep Variables1:53
Clean up your dataset by removing unnecessary variables. This video explains the crucial drop and keep commands. We'll show you how to use drop to remove a few specific variables and how to use the safer keep command to retain only the variables you need. Master these essential commands to streamline your data cleaning workflow.
- How to drop and keep Cases4:05
Learn how to filter your data to include only the observations you need. This video covers how to use the drop and keep commands with if conditions to remove or retain specific cases (rows) in your dataset. You'll learn how to handle missing data and other conditions to ensure your analysis is based on the correct subset of your data.
- Rename Variable in Stata2:25
Are your variable names cryptic or inconsistent? This video shows you how to easily rename variables in Stata. We'll cover the rename command for changing one variable at a time and the renvars command for renaming multiple variables based on a common pattern. This is a must-watch for anyone who wants to improve the readability and consistency of their dataset
- Missing value in Stata5:41
Missing data is a common challenge in data analysis. This video provides a comprehensive guide to identifying and handling missing values in Stata. You'll learn how Stata represents missing data with the dot (.) and how to use the tabulate and mvdecode commands to check for and recode missing values. We'll also discuss best practices for dealing with missing data to avoid biased results.
- Importing Data from Excel into Stata5:01
In this video, you will learn how to easily import datasets from Microsoft Excel into Stata. We will cover:
Preparing your Excel file for import
Using Stata’s menu and commands to load Excel data
Checking your imported dataset for accuracy
Saving the data in Stata format for future use
By the end, you will be able to bring any Excel dataset into Stata smoothly and get it ready for analysis.
- Generating New Variables in Stata7:53
In this video, you will learn how to create new variables in Stata for your analysis. We will cover:
Using the generate command to create numeric and string variables
Creating variables based on calculations or conditions
Checking your new variables in the dataset
Tips to avoid common mistakes when generating variables
By the end, you will be able to create meaningful new variables to enrich your data analysis in Stata.
- Creating Graphs in Stata5:07
In this video, you will learn how to create clear and informative graphs in Stata to visualize your data. We will cover:
Plotting basic graphs such as bar charts, histograms, and scatter plots
Customizing graph titles, labels, and colors
Saving and exporting graphs for reports or presentations
Tips for choosing the right type of graph for your data
By the end, you will be able to create professional-looking graphs in Stata that make your analysis easier to understand and share.
- Data Analysis Part 1: Descriptive and Inferential Statistics in Stata7:10
In this video, you will learn how to perform both descriptive and inferential statistics in Stata. We will cover:
Understanding the difference between descriptive and inferential analysis
Running descriptive statistics to summarize your data
Performing basic inferential tests to draw conclusions from your data
Interpreting Stata output in simple terms
By the end, you will know how to use Stata to both describe your dataset and make statistical inferences for research and decision-making.
- Data Analysis Part 2: Linear Regression in Stata5:35
In this video, you will learn how to run regression analysis in Stata to explore relationships between variables. We will cover:
Understanding the purpose of regression analysis
Running simple and multiple linear regression in Stata
Interpreting regression coefficients and p-values
By the end, you will be able to perform regression analysis in Stata and interpret the results with confidence.
- Data Analysis Part 3: Logistic regression6:22
In this video, you will learn how to perform logistic regression in Stata to analyze binary outcome variables. We will cover:
Understanding when to use logistic regression
Running simple and multiple logistic regression in Stata
Interpreting odds ratios, confidence intervals, and p-values
Checking model fit and diagnostics
Saving and exporting your results for reports or publications
By the end, you will be able to run logistic regression in Stata and interpret the results effectively for research or professional projects.
- Introduction to NFHS Data5:22
In this lecture, you will learn what NFHS data is, its structure, and how it is used in research and public health analysis.
- Selecting Variables for Research4:15
Learn how to identify and select relevant variables from NFHS datasets based on your research objectives.
- Handling Extreme Values in Stata7:08
This lecture shows how to detect extreme or outlier values and convert them into meaningful or missing values for accurate analysis.
- Setting Decimal Points and Creating New Variables6:48
You will learn how to adjust decimal values and create new variables required for analysis using Stata.
- Understanding Nutritional Variables6:07
This lecture explains key nutritional variables in NFHS data and how to interpret them for research
- Maternal ANC and Undernutrition8:43
Learn how to work with maternal health variables such as antenatal care (ANC) and undernutrition indicators.
- Keeping and Ordering Variables1:55
This lecture covers how to keep only necessary variables and organize them efficiently for analysis.
- Renaming Variables in Stata3:04
Learn how to rename variables clearly to improve readability and make your dataset more user-friendly.
- Saving a Clean Dataset2:21
In this lecture, you will learn how to save a clean and ready-to-use dataset for further analysis and research.
- Univariate Analysis: Percentages, Mean, and Standard Deviation6:29
Learn how to summarize variables using percentages, mean, and standard deviation in Stata.
- Cross-tabulation in Stata3:08
This lecture shows how to perform cross-tabulation to explore relationships between categorical variables.
- Mean Comparison by Categories (t-test)3:41
Learn how to compare mean values across groups using t-tests in Stata.
- Proportion and Confidence Interval (bprop)2:01
This lecture explains how to calculate proportions and their confidence intervals using the bprop command.
- Mean and Confidence Interval (amean CI)2:27
Learn how to estimate mean values along with confidence intervals for better interpretation.
- Arithmetic, Geometric, Harmonic, and Adjusted Means in Stata2:54
In this lecture, you will learn different types of means used in data analysis, including arithmetic, geometric, harmonic, and adjusted means. You will also learn how to calculate these measures in Stata and understand when to use each one.
- Descriptive Analysis with Sampling Weights4:51
Learn how to apply sampling weights in NFHS data to produce accurate and representative results.
- Introduction to One-Way ANOVA2:35
Learn when and why to use one-way ANOVA for comparing means across groups.
- Assessing Distribution: Histogram and Box Plot3:17
This lecture shows how to check data distribution using histograms and box plots before analysis.
- One-Way ANOVA in Stata2:54
Learn how to perform one-way ANOVA in Stata and interpret the results.
- Introduction to Two-Way ANOVA2:00
Understand the concept of two-way ANOVA and when to use it.
- Two-Way ANOVA: Main Effects2:14
Learn how to interpret main effects in two-way ANOVA.
- Two-Way ANOVA: Interaction Effects1:07
This lecture explains interaction effects and how variables influence each other.
- Two-Way ANOVA: Combined Model (Main + Interaction)1:15
Learn how to run and interpret a full two-way ANOVA model with both main and interaction effects.
- Marginal Means in Stata3:17
- ANOVA with Sampling Weights3:42
Understand how to apply sampling weights in ANOVA for survey data like NFHS.
- Setting an Objective of Regression Analysis1:09
Understand the purpose of regression analysis and how it is used in research.
- Defining Variables for Logistic Regression9:13
Learn how to define outcome, exposure, and covariates for logistic regression models.
- Simple Logistic Regression in Stata4:38
Perform basic logistic regression and understand model output.
- Interpreting Log Odds and Odds Ratios2:54
Learn how to interpret coefficients, odds ratios, confidence intervals, and p-values.
- Multiple Logistic Regression in Stata8:21
Build adjusted models by including multiple variables
- Logistic Regression with Sampling Weights3:45
Learn how to apply sampling weights for survey data like NFHS.
- Adjusting for Clustering in Logistic Regression3:27
Understand how to adjust for cluster effects in survey data.
- Survey Logistic Regression (svy: logit)3:27
Perform logistic regression using survey design (weights, strata, clusters).
- Multilevel Logistic Regression in Stata7:08
Learn how to run multilevel (mixed-effects) logistic regression models.
Requirements
- No prior experience with Stata is needed
- A computer with Stata installed (any version works)
Description
This course is a practical, step-by-step guide to data analysis in Stata using National Family Health Survey (NFHS-India) data. It is designed for beginners, students, and researchers who want to learn Stata for real-world survey data analysis, especially using DHS/NFHS datasets.
The course begins with the basics of Stata, including data management, data cleaning, variable creation, and descriptive statistics. You will learn how to import data from Excel, and Stata files, handle missing values, label variables, and prepare datasets for analysis.
After building a strong foundation, the course moves to NFHS-India data analysis, where you will work with real survey data. You will learn how to understand NFHS data structure, select relevant variables, and create key variables such as outcomes and exposures.
You will then perform essential statistical analysis in Stata, including descriptive analysis, data visualization, bivariate analysis, and regression models such as logistic and linear regression. You will also learn how to interpret odds ratios, confidence intervals, and p-values for research reporting.
This course focuses on hands-on learning with real examples, making it useful for academic research, thesis work, public health studies, and survey data analysis.
By the end of this course, you will be able to confidently analyze NFHS/DHS data using Stata and apply your skills in real research projects. No prior experience with Stata is required.
Who this course is for:
- Master’s and PhD students who need to analyse data for their research
- Beginners who want to learn Stata step by step