PFT1981: Data: Charnes, Cooper and Rhodes (1981).

Description

Data from Project Follow Through (PTF) in public school education. There are 49 DMUs (school sites) in PFT and 21 DMUs in Non-Follow Through (NFT). Authors consider 3 outputs (Y) and 5 inputs (X).

Usage

data("PFT1981")

Arguments

Format

Data frame with 70 rows and 10 columns. Definition of inputs (X) and outputs (Y):

Y1 = Reading: Total Reading Scores (as measured by the Metropolitan Achievement Test).
Y2 = Math: Total Math Scores (total mathematics score by the Metropolitan Achievement Test.
Y3 = Coopersmith: Total Coopersmith Scores (Coopersmith self-esteem inventory, intended as a measure of self-esteem).
X1 = Education: Education level of mother (as measured in terms of percentage of high school graduates among female parents).
X2 = Occupation: Occupation Index (highest occupation of a family member according to a pre-arranged rating scale).
X3 = Parental: Parental Visit Index (representing the number of visits to the school site).
X4 = Counseling: Counseling Index (parent counselling index calculated from data on time spent with child on school-related topics such as reading together, etc.).
X5 = Teachers: Number of Teachers (number of teachers at a given site).
Program: PFT or NFT.

Author

Vicente Coll-Serrano (vicente.coll@uv.es). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolos (vicente.bolos@uv.es). Department of Business Mathematics

Rafael Benitez (rafael.suarez@uv.es). Department of Business Mathematics

University of Valencia (Spain)

Examples

Run this code

# Example 1. Replication of results in Charnes, Cooper and Rhodes (1981)
data("PFT1981")
# selecting DMUs in Project Follow Through (PFT)
PFT <- PFT1981[1:49, ]
PFT <- make_deadata(PFT,
                    dmus = 1,
                    inputs = 2:6,
                    outputs = 7:9 )
eval_pft <- model_basic(PFT,
                        orientation = "io",
                        rts = "crs")
eff_pft <- efficiencies(eval_pft)

# Example 2. Replication of results in Charnes, Cooper and Rhodes (1981)
data("PFT1981")
# selecting DMUs in Non-Follow Through (NFT)
NFT <- PFT1981[50:70,]
NFT <- make_deadata(NFT,
                    dmus = 1,
                    inputs = 2:6,
                    outputs = 7:9 )
eval_nft <- model_basic(NFT,
                        orientation = "io",
                        rts = "crs")
eff_nft <- efficiencies(eval_nft)