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The dropout package offers robust tools for dropout analysis in survey data. It helps you identify and handle incomplete responses effectively to ensure the quality of your research findings.


You can install the development version of dropout from GitHub using the following command:

# Install the released version from CRAN

# development version from GitHub:


  • drop_detect: Detects participants who drop out of the survey by recognizing NA sequences up to the last question of the survey. Additionally, the function provides the column name and index where the dropout occurs.

  • dropout_summary: Offers a high-level summary of dropout occurrences, providing key statistics to understand the patterns of participant dropouts across different survey questions.

Using drop_detect

library(dplyr) # not necessary, but recommended

# Detect dropouts in the 'flying' dataset up to the column "location_census_region"
drop_detect(flying, "location_census_region") %>%
  bind_cols(flying, .) %>%
  filter(dropout == FALSE | dropout_index > 22)

Using dropout_summary


# Summarizing dropouts in the 'flying' dataset up to the column "location_census_region"
dropout_summary(flying, "location_census_region")

Further Reading

For more details, practical examples, and tips on interpreting summary statistics, please refer to the package vignette.