example_annik

example_annik.r

participant_id <- c(1,1,2,2,3,3,3,4,4)
answer1 <- c(12,123,33,333,3,22,11,32,12)
answer2 <- c(12,123,33,333,3,22,11,22,11)
results <- data.frame(participant_id, answer1, answer2)
# Results looks like this:
# participantId answer1 answer2
# 1              1       12       12
# 2              1      123      123

unique_participant_ids <- unique(results$participant_id)
# unique_participant_ids looks like "[1] 1 2 3 4"
intercept_per_participant <- c()
for (participantId in unique_participant_ids) { # Iterate over all participants
    all_answers_for_participant <- subset(results, participant_id == participantId) # Get only the answers from the current participant

    # fit here your model with "all_answers_for_participant"
    # E.g. https://stackoverflow.com/questions/23240182/deciding-threshold-for-glm-logistic-regression-model-in-r

    model <- lm(all_answers_for_participant$answer1 ~ all_answers_for_participant$answer2) # I use LM as an example
    model_summary <- summary(model)
    intercept_value <- model_summary$coefficients[1,1]
    intercept_per_participant <- c(intercept_per_participant, intercept_value) # Append the interesting things to a list (here intercept)
}

# Now do something with your data
# E.g. get the man of all intercepts..
mean(intercept_per_participant)