AAPOR Survey Outcome Rates

Standardized survey outcome rate functions, including the response rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow survey researchers to measure the quality of survey data using definitions published by the American Association of Public Opinion Research (AAPOR). For details on these standards, see AAPOR (2016) < https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.

Coveragestatus Travis buildstatus Ropenscistatus

outcomerate is a lightweight R package that implements the standard outcome rates for surveys, as defined in the Standard Definitions of the American Association of Public Opinion Research (AAPOR).

Although the mathematical formulas are straightforward, it can get tedious and repetitive calculating all the rates by hand, especially for sub-groups of your study. The formulas are similar to one another and so it is also dangerously easy to make a clerical mistake. The outcomerate package simplifies the analytically workflow by defining all formulas as a collection of functions.


The latest development version is available via github:



Let’s say you try to survey 12 people. After finishing the fieldwork, you tabulate all your attempts into a table of disposition outcomes:

code disposition n
I Complete interview 4
P Partial interview 2
R Refusal and break-off 1
NC Non-contact 1
O Other 1
UH Unknown if household 1
NE Known ineligible 1
UO Unknown, other 1

Using this table, you may wish to report some of the common survey outcome rates, such as:

  • Response Rate: The proportion of your sample that results in an interview.
  • Cooperation Rate: The proportion of people contacted who participate in your survey.
  • Refusal Rate: The proportion of your sample that refused to participate.
  • Contact Rate: The proportion of sampled cases where you manage to reach the respondent.
  • Location Rate: The proportion of cases (say, in an establishment survey) that you manage to locate.

Most of these rates come under a number of variants, having definitions that are standardized by AAPOR. The outcomerate function lets your calculate these rates seamlessly:

# load package
# set counts per disposition code (needs to be a named vector)
freq <- c(I = 4, P = 2, R = 1, NC = 1, O = 1, UH = 1, UO = 1, NE = 1)
# calculate rates, assuming 90% of unknown cases are elligble
outcomerate(freq, e = eligibility_rate(freq))
#>   RR1   RR2   RR3   RR4   RR5   RR6 COOP1 COOP2 COOP3 COOP4  REF1  REF2 
#> 0.364 0.545 0.370 0.556 0.444 0.667 0.500 0.750 0.571 0.857 0.091 0.093 
#>  REF3  CON1  CON2  CON3  LOC1  LOC2 
#> 0.111 0.727 0.741 0.889 0.818 0.833

Dispositions do not always come in a tabulated format. Survey analysts often work with microdata directly, where each row represents an interview. The outcomerate package allows you to obtain rates using such a format as well:

# define a vector of dispositions
x <- c("I", "P", "I", "UO", "R", "I", "NC", "I", "O", "P", "UH")
# calculate desired rates
outcomerate(x, rate = c("RR2", "CON1"))
#>  RR2 CON1 
#> 0.55 0.73
# obtain a weighted rate
w <- c(rep(1.3, 6), rep(2.5, 5))
outcomerate(x, weight = w, rate = c("RR2", "CON1"))
#>  RR2w CON1w 
#>  0.50  0.69



outcomerate 1.0.1


  • Added CITATION details to the package

outcomerate 1.0.0

New Features

  • eligibility_rate() function added to estimate the proportion of eligible cases from the unknowns, based on the known ineligibles (NE's).


  • Refactoring of code based on ROpenSci peer review feedback.
  • Added S3 method for factors.
  • Addition of many more unit tests.
  • Addtional of more helpful error messages.

Breaking Changes

  • weight argument no longer accepts scalar inputs.
  • If weights are provided, the output labels are renamed in the form 'RR2w' instead of "RR2"
  • If rate = NULL in the function parameters, the default behavior will be to return all possible rates given the other parameters specified.
  • Disposition codes now accept "NE" for known ineligibles. Within outcomerate(), these are largely ignored, but are used by eligibility_rate() to estimate e


  • Added documentation for the (internal) fmat formula matrix object
  • Added documentation on the middleearth toy dataset


  • Created outcomerate package

Reference manual

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1.0.1 by Rafael Pilliard Hellwig, 3 years ago


Report a bug at https://github.com/ropensci/outcomerate/issues

Browse source code at https://github.com/cran/outcomerate

Authors: Rafael Pilliard Hellwig [aut, cre] , Carl Ganz [rev] , Neal Richardson [rev]

Documentation:   PDF Manual  

CC0 license

Imports Rdpack, stats

Suggests dplyr, forcats, ggplot2, knitr, testthat, tidyr, covr, rmarkdown, spelling, stringr

See at CRAN