| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ~Get Your Files Here ! | |||
| 1 - Introduction to RStudio for DHS Data Analysis | |||
| 1. Welcome to RStudio for DHS Data Analysis.mp4 | 33.4 MB | ||
| 10 - Linear Regression in RStudio for Public Health Research | |||
| 11 - Survey Weighted Logistic Regression (svy) in RStudio | |||
| 2 - Reading and Understanding DHS Data and Codebooks (Multi Country) | |||
| 3 - Preparing Nutritional Indicators from DHS Data Stunting Wasting &Underweigt | |||
| 10. Choosing DHS Variables for Nutritional Indicators and Covariates CodeBook.mp4 | 59.1 MB | ||
| 11. Preparing Factor (Categorical) Variables and Value Labels.mp4 | 46.8 MB | ||
| 12. Preparing Numerical (Continuous) Variables from the DHS Dataset.mp4 | 42.1 MB | ||
| 13. Identifying Unusual extreme Values and Correcting Decimal Points.mp4 | 45.7 MB | ||
| 14. Replacing Extreme and Unusual Values with Missing and Generating New Variables.mp4 | 82 MB | ||
| 15. Generating Nutritional Indicators Stunting Wasting and Underweight.mp4 | 72.7 MB | ||
| 16. Finalizing the Variable List for Analysis Nutritional and covariates.mp4 | 33.1 MB | ||
| 17. Short Summary of Updated Variables Review of Finalized and Updated Variables.mp4 | 33.8 MB | ||
| 18. Modifying Value Labels for Factor Variables.mp4 | 100.6 MB | ||
| 19. Renaming Variables Based on Variable Names and Meaning.mp4 | 71.2 MB | ||
| 20. Adding Variable Labels to the Current Dataset.mp4 | 117.2 MB | ||
| 21. Saving the Dataset in RData Format.mp4 | 33.2 MB | ||
| 4 - Descriptive Univariate & Bivariate Analysis with Statistical Tests (Unweighted) | |||
| 22. Univariate Descriptive Statistics (Unweighted Analysis) gtsummary.mp4 | 52.5 MB | ||
| 22. Univariate Descriptive Statistics (Unweighted Analysis) gtsummary_Resource_Nutrition DHS Desc pval R.R | 3.7 KB | ||
| 23. Formatting Categorical Variables as n (%).mp4 | 25.3 MB | ||
| 24. Formatting Continuous Variables as Mean ± Standard Deviation.mp4 | 15.9 MB | ||
| 25. Setting Decimal Places for Statistical Results.mp4 | 27.4 MB | ||
| 26. Bivariate Analysis Using Column Percentages (Unweighted).mp4 | 15.6 MB | ||
| 27. Adding Overall Findings to Bivariate Tables.mp4 | 60.2 MB | ||
| 28. Adding p Values Using t Test and Chi Square Test (Unweighted).mp4 | 41.7 MB | ||
| 29. Exporting Publication Ready Tables to MS Word.mp4 | 48 MB | ||
| 5 - Descriptive Univariate & Bivariate Analysis Survey Weigthed p value | |||
| 30. Setting Up Survey Design (svyset svydesign).mp4 | 33 MB | ||
| 30. Setting Up Survey Design (svyset svydesign)_Resource_Nutrition DHS SVY Desc pval R.R | 3.2 KB | ||
| 31. Univariate Descriptive Statistics (Survey Weighted).mp4 | 24.1 MB | ||
| 32. Checking Findings Against Published Reports.mp4 | 12.7 MB | ||
| 33. Table Formatting – n (%) and Mean ± SD (Survey Weighted).mp4 | 47.5 MB | ||
| 34. Survey Weighted Bivariate Analysis (svy).mp4 | 37.4 MB | ||
| 35. Survey Weighted Chi Square Test and p Value (svy).mp4 | 70.5 MB | ||
| 36. Exporting Survey Weighted Tables to MS Word (Publication Ready).mp4 | 48.1 MB | ||
| 6 - Bar Diagrams for Categorical Variables in RStudio (ggplot2) | |||
| 37. Bar Diagram for a Single Categorical Variable.mp4 | 59.8 MB | ||
| 37. Bar Diagram for a Single Categorical Variable_Resource_Nutrition DHS graph bar R.R | 5.2 KB | ||
| 38. Bar Diagram for a Single Categorical Variable – Customization & Labeling.mp4 | 58.9 MB | ||
| 39. Bar Diagram for Two Categorical Variables (Grouped Bar Chart).mp4 | 93.6 MB | ||
| 7 - Bar Diagrams for Binary Variables in RStudio (ggplot2) | |||
| 40. Bar Diagram for a Binary Variable by One Categorical Variable.mp4 | 82.8 MB | ||
| 41. Bar Diagram for a Binary Variable by Two Categorical Variables.mp4 | 141.6 MB | ||
| 42. Removing Background and Using Clean Themes in ggplot2.mp4 | 27.9 MB | ||
| 43. Bar Diagram for Multiple Binary Variables.mp4 | 168.8 MB | ||
| 44. Exporting Figures to a Folder in RStudio (Publication Ready).mp4 | 61.3 MB | ||
| 8 - Box Plots for Continuous Variables in RStudio (ggplot2) | |||
| 45. Box Plot for a Single Continuous Variable.mp4 | 20.4 MB | ||
| 45. Box Plot for a Single Continuous Variable_Resource_Nutritio DHS box R.R | 1.8 KB | ||
| 46. Box Plot for a Single Continuous Variable – Labeling & Customization.mp4 | 52.3 MB | ||
| 47. Box Plot for a Single Continuous Variable by One Categorical Variable.mp4 | 29.2 MB | ||
| 48. Box Plot for a Single Continuous Variable by Two Categorical Variables.mp4 | 22.7 MB | ||
| 49. Modifying and Labeling Box Plots for Publication Ready Graphics.mp4 | 87.2 MB | ||
| 9 - Logistic Regression in RStudio Using the gtsummary Package | |||
| 50. Defining the Outcome Variable for Logistic Regression.mp4 | 21.2 MB | ||
| 50. Defining the Outcome Variable for Logistic Regression_Resource_logit R.R | 7.3 KB | ||
| 51. Simple Logistic Regression (Unadjusted Odds Ratio).mp4 | 65 MB | ||
| 52. Multiple Logistic Regression (Adjusted Odds Ratios).mp4 | 29.3 MB | ||
| 53. Changing Reference Categories for Categorical Independent Variables.mp4 | 65.9 MB | ||
| 54. Recap – Variable Modification for Logistic Regression.mp4 | 86.3 MB | ||
| 55. Publication Ready Table for Unadjusted Odds Ratios.mp4 | 133.1 MB | ||
| 56. Publication Ready Table for Adjusted Odds Ratios (AOR).mp4 | 54.9 MB | ||
| 57. Final – Publication Ready Table (Unadjusted & Adjusted Odds Ratios).mp4 | 28.7 MB | ||
| 58. Saving Publication Ready Tables in MS Word.mp4 | 34.2 MB | ||
| 59. Factors Associated with Stunting Underweight and Wasting.mp4 | 121.5 MB | ||
| 9. Key DHS Variables for Stunting Wasting and Underweight.mp4 | 30.7 MB | ||
| 9. Key DHS Variables for Stunting Wasting and Underweight_Resource_Nutrition DHS DataManagement R.R | 3.7 KB | ||
| 3. Importing Tanzania DHS Data from Stata ( dta) Files.mp4 | 20.1 MB | ||
| 3. Importing Tanzania DHS Data from Stata ( dta) Files_Resource_Read DHS R.R | 716.8 B | ||
| 4. Importing Tanzania DHS Data from SPSS ( sav) Files.mp4 | 17.5 MB | ||
| 5. Reading DHS Data from Other Countries (Peru Ethiopia).mp4 | 35.5 MB | ||
| 6. Understanding DHS Variables Using Codebooks.mp4 | 69.6 MB | ||
| 6. Understanding DHS Variables Using Codebooks_Resource_CodeBook docx.docx | 171.9 KB | ||
| 7. Selecting Variables Using the select() Function (Examples).mp4 | 60.9 MB | ||
| 8. Creating a Short Summary Table Using the gtsummary Package.mp4 | 12.1 MB | ||
| 63. Defining Survey Design for Logistic Regression.mp4 | 33.1 MB | ||
| 63. Defining Survey Design for Logistic Regression_Resource_svy logit R.R | 3.4 KB | ||
| 64. Survey Weighted Simple Logistic Regression.mp4 | 28.7 MB | ||
| 65. Survey Weighted Multiple Logistic Regression.mp4 | 18.5 MB | ||
| 66. Changing Reference Categories in svy Models.mp4 | 38.6 MB | ||
| 67. Publication Ready Tables for svy Logistic Regression Crude Odds Ratio.mp4 | 93.4 MB | ||
| 68. Publication Ready Tables for svy Logistic Regression Adjusted Odds Ratios.mp4 | 39.4 MB | ||
| 69. Final publication ready Table and Exporting svy Logistic Regression to MS Word.mp4 | 53 MB | ||
| 60. Defining the Outcome and Independent Variables.mp4 | 21.4 MB | ||
| 61. Simple Linear Regression.mp4 | 30.4 MB | ||
| 62. Multiple Linear Regression.mp4 | 29.5 MB | ||
| 2. Course Overview RStudio Statistics & Publication Workflow.mp4 | 88.3 MB |
Demographic and Health Survey Data Analysis in R and RStudio
https://WebToolTip.com
Published 12/2025
Created by Md Ahshanul Haque
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 69 Lectures ( 5h 23m ) | Size: 3.51 GB
Practical Survey Data Analysis Using RStudio & R with DHS Data for Public Health Research
What you'll learn
Import, understand, and manage graphic and Health Survey (DHS) data in R and RStudio
Perform descriptive and exploratory analysis of DHS survey data using R
Apply survey design concepts and conduct survey-weighted analyses in R
Analyze key public health topics (childhood malnutrition, maternal health, child feeding, women’s empowerment) using DHS data
Produce clean, reproducible, and publication-ready tables and results from DHS data
Requirements
Basic familiarity with R and RStudio is helpful but not mandatory
A computer with R and RStudio installed
Interest in data analysis, public health, or survey data
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