apollo_drugChoiceData: Simulated dataset of medication choice.

Description

A simulated dataset containing 10,000 stated medication choices among four alternatives.

Usage

apollo_drugChoiceData

Arguments

Format

A data frame with 10000 rows and 33 variables:

ID: Numeric. Identification number of the individual.
task: Numeric. 1 if the row corresponds to a revealed preference (RP) observation. 0 otherwise.
best: Numeric. Consecutive ID of RP observation.
second_pref: Numeric. 1 if the row corresponds to a stated preference (SP) observation. 0 otherwise.
third_pref: Numeric. Consecutive ID of SP choice task.
worst: Numeric. Access time (in minutes) of mode air.
brand_1: Character. Name of alternative's brand.
country_1: Character. Name of alternative's country of origin.
char_1: Character. Characteristics of the alternative (standard, fast acting, or double strength).
side_effects_1: Numeric. Chance of suffering negative side effects if this alternative is consumed.
price_1: Numeric. Cost of this alternative in Pounds sterling (GBP).
brand_2: Character. Name of alternative's brand.
country_2: Character. Name of alternative's country of origin.
char_2: Character. Characteristics of the alternative (standard, fast acting, or double strength).
side_effects_2: Numeric. Chance of suffering negative side effects if this alternative is consumed.
price_2: Numeric. Cost of this alternative in Pounds sterling (GBP).
brand_3: Character. Name of alternative's brand.
country_3: Character. Name of alternative's country of origin.
char_3: Character. Characteristics of the alternative (standard, fast acting, or double strength).
side_effects_3: Numeric. Chance of suffering negative side effects if this alternative is consumed.
price_3: Numeric. Cost of this alternative in Pounds sterling (GBP).
brand_4: Character. Name of alternative's brand.
country_4: Character. Name of alternative's country of origin.
char_4: Character. Characteristics of the alternative (standard, fast acting, or double strength).
side_effects_4: Numeric. Chance of suffering negative side effects if this alternative is consumed.
price_4: Numeric. Cost of this alternative in Pounds sterling (GBP).
regular_user: Numeric. 1 if the respondent is a regular user of headache medicine, 0 otherwise.
university_educated: Numeric. 1 if the respondent holds a university degree, 0 otherwise.
over_50: Numeric. 1 if the respondent is 50 years old or older, 0 otherwise.
attitude_quality: Numeric. Level of agreement from 1 (strongly disagree) to 5 (strongly agree) with the phrase 'I am concerned about the quality of drugs developed by unknown companies'.
attitude_ingredients: Numeric. Level of agreement from 1 (strongly disagree) to 5 (strongly agree) with the phrase 'I believe that ingredients are the same no matter what brand'.
attitude_patent: Numeric. Level of agreement from 1 (strongly disagree) to 5 (strongly agree) with the phrase 'The original patent holders have valuable experience with their medicines'.
attitude_dominance: Numeric. Level of agreement from 1 (strongly disagree) to 5 (strongly agree) with the phrase 'I believe the dominance of big pharmaceutical companies is unhelpful'.

Details

This dataset is to be used for discrete choice modelling. Data comes from 1,000 individuals, each with ten stated preferences (SP) observations among headache medication. There are 10,000 choices in total. Data is simulated. Each observation contains attributes of the alternatives, characteristics of the respondent, and their answers to four attitudinal questions. All four alternatives are always available for all individuals. Alternatives 1 and 2 are branded, while alternatives 3 and 4 are generic. Respondents provide a full ranking of alternatives for each choice task (i.e. observation).