drugcost: Drug cost.

In alr4: Data to Accompany Applied Linear Regression 4th Edition

Description

These data are to try to understand the effect of health plan characteristics on drug costs. Health plans vary in size, given as member months. Some plans use generic drugs more than others. All differ on copayments. Some have strong restrictions on which drugs can be dispensed value of RI=0 means that all drugs are dispensed, RI=100 means that only one per category is avaiable. The goal is to determine the terms that are related to cost, and in particular to understand the role of GS and RI in determining cost.

Format

This data frame uses a short code name for the drug plan as row labels and contains the following columns:

COST

Ave. cost to plan for 1 prescription for 1 day

RXPM

Number of prescriptions per member per year

GS

Percent generic substitution, number between 0 (no substitution) to 100 (always use generic substitute)

RI

Restrictiveness index (0=none, 100=total)

COPAY

Average Rx copayment

AGE

Average age of member

F

Percent female members

MM

Member months, a measure of the size of the plan

Source

Mark Siracuse

References

Weisberg, S. (2014). Applied Linear Regression, 4th edition. Hoboken NJ: Wiley.

Examples

head(drugcost)

Example output

Loading required package: car
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    COST RXPM GS   RI COPAY  AGE    F      MM
MN1 1.34  4.2 36 45.6 10.87 29.7 52.3 1158096
MN2 1.34  5.4 37 45.6  8.66 29.7 52.3 1049892
MN3 1.38  7.0 37 45.6  8.12 29.7 52.3   96168
GA  1.22  7.1 40 23.6  5.89 28.7 53.4  407268
GA2 1.08  3.5 40 23.6  6.05 28.7 53.4   13224
AZ1 1.16  7.2 46 22.3  5.05 29.1 52.2  303312

alr4 documentation built on May 2, 2019, 6:40 p.m.