PFT1981 {deaR}

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")

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(s)

Vicente Coll-Serrano ([e-mail]). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolos ([e-mail]). Department of Business Mathematics

Rafael Benitez ([e-mail]). Department of Business Mathematics

University of Valencia (Spain)

Source

Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through", Management Science, 27(6), 668-697. doi:10.1287/mnsc.27.6.668

See Also

make_deadata, model_basic

Examples

# 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)