Introduction

This R Markdown document processes survey data from KoboToolbox, cleans it, and prepares it for analysis. The data contains baseline, midline, and endline survey responses from a multi-year project.

Install and Load Required Packages

Fetch Data from KoboToolbox API

Initial Data Cleaning

Rename Variables

Create Survey Period Classification

Data Correction and Standardization

Create Unique ID and Fix Missing Values

Create Feature Variables

Remove Duplicates

Fix Missing Values in Age, Gender, and Fishing Role

Recode Disposition and Field Interviewer Names

Save and Export Data

Field Interviewer Performance Report

This table shows the survey accomplishment by field interviewer.

Survey Disposition
 Total
Completed For Callback Refused at first attempt Refused after 2x callback Invalid
Field Interviewer





    Ailene Gongora 112 (8.5%) 23 (1.7%) 0 (0%) 11 (0.8%) 12 (0.9%) 158 (12%)
    Fralene Regis 102 (7.8%) 21 (1.6%) 0 (0%) 2 (0.2%) 9 (0.7%) 134 (10%)
    Joann Maiz 86 (6.5%) 72 (5.5%) 3 (0.2%) 5 (0.4%) 12 (0.9%) 178 (14%)
    Jonas Malingin 93 (7.1%) 27 (2.1%) 3 (0.2%) 3 (0.2%) 23 (1.7%) 149 (11%)
    Lailah Ortega 97 (7.4%) 9 (0.7%) 1 (<0.1%) 2 (0.2%) 1 (<0.1%) 110 (8.4%)
    Lourdes Pobe 35 (2.7%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 35 (2.7%)
    Marrian Jazzmean Rama 93 (7.1%) 10 (0.8%) 0 (0%) 2 (0.2%) 3 (0.2%) 108 (8.2%)
    Michael Lapu-lapu 119 (9.0%) 14 (1.1%) 1 (<0.1%) 2 (0.2%) 0 (0%) 136 (10%)
    Nelson Baliad 80 (6.1%) 56 (4.3%) 0 (0%) 5 (0.4%) 10 (0.8%) 151 (11%)
    Ray Paul Madaje 82 (6.2%) 48 (3.6%) 2 (0.2%) 18 (1.4%) 3 (0.2%) 153 (12%)
    tabex 4 (0.3%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 4 (0.3%)
Total 903 (69%) 280 (21%) 10 (0.8%) 50 (3.8%) 73 (5.5%) 1,316 (100%)