cjoint (version 1.0.2)

read.qualtrics: Read Data from a Conjoint Qualtrics Experiment

Description

Converts the raw .CSV data file downloaded from an online conjoint experiment run using the Qualtrics survey software into a data frame usable by the amce routine. Each row of the Qualtrics .CSV file is a single survey respondent. The rows of the resulting dataframe correspond to individual profile choices. Currently, this function only works for designs with a binary outcome variable (selected/not selected) that requires a single choice among profiles.

Usage

read.qualtrics(filename, responses, covariates = NULL, respondentID = NULL)

Arguments

filename

A .CSV file containing responses exported from a Qualtrics survey experiment. The first row contains question and variable identifiers (e.g. V1, Q1). The second row contains variable names and question texts. Subsequent rows contain the answers of each re

responses

A character or integer vector with the identifiers of the CSV columns that contain the conjoint responses. The first element corresponds to the identifier of the first question, the second element corresponds to the second question and so on. The length o

covariates

A character vector denoting the column names of any other respondent-level characteristics measured in the survey that should be included in the resulting dataframe.

respondentID

A character string denoting a column containing a unique identifier for each respondent (e.g. an IP address). This identifier will be carried over into the output. If NULL, each respondent will be given an arbitrary identifier in the output dataframe. Lea

Value

• A dataframe in which each row corresponds to a single profile. The column "selected" denotes whether that profile was selected by the respondent. The columns "respondent" and "task" denote the respondent and task numbers to which the profile was assigned. Respondent-level covariates are appended to each row.

Details

This function currently only works with experiments that generate profiles using .PHP scripts created by the Conjoint Survey Design Tool. It also is only able to handle standard conjoint designs (binary outcome variable/forced choice). (http://scholar.harvard.edu/astrezhnev/conjoint-survey-design-tool). For each respondent in the .CSV file, attribute and level names are stored using the following naming convention: Level Name: F-[task number]-[profile number]-[attribute number] Attribute Name: F-[task number]-[attribute number] Example: F-1-3-2 denotes the level corresponding to Task 1, Profile 3, Attribute 2 F-3-3 denotes the attribute name corresponding to Task 3, Attribute 3

References

Strezhnev, A., Hainmueller, J., Hopkins, D., and Yamamoto, T. (2014) Conjoint Survey Design Tool. http://scholar.harvard.edu/astrezhnev/conjoint-survey-design-tool

Examples

# An example file with 5 conjoint tasks per respondent and a single covariate
# You can demonstrate this function's output using the CandidateConjointQualtrics.csv 
# demonstration file in the 'inst' subdirectory
conjoint_data <- read.qualtrics("CandidateConjointQualtrics.csv", 
responses=c("Q2.3", "Q2.7", "Q2.10", "Q2.13", "Q2.16"), 
covariates=c("Q6.6"), respondentID="V1")