Wide-form input logistic regression

The second and third approaches for fitting logistic regressions require "wide" format data:

      x fail success Total successProportion
    1 a   12       2    14         0.1428571
    2 b    3      11    14         0.7857143

For the second approach, model a 2 column matrix of successes and failures (e.g., number of no's and yes's per group).

In this format, use the formula cbind(success, fail) ~ predictor.

For the third approach, model the probability of success (e.g., group 1 had 75% yes and group 2 had 65% no) and the weight or number of observations per group (e.g., there were 40 individuals in group 1 and 100 individuals in group 2).

In this format, the formula proportion of successes ~ response variable is used with weights = number in treatment.

Fit a logistic regression using the data.frame dataWide. First, combine success and fail with cbind() and then have this predicted by x. Save the output as lr_2
Fit a logistic regression using the data.frame dataWide with successProportion being predicted by x while using weights = Total. Save the output as lr_3

Take Hint (-30 XP)

Exercise

Wide-form input logistic regression

Instructions