Program Effectiveness Data

Data used to study the effectiveness of a program.

Usage

data("ProgramEffectiveness")

Format

A data frame containing 32 cross-section observations on 4 variables.

grade

Factor with levels "increase" and "decrease".

average

Grade-point average.

testscore

Test score on economics test.

participation

Factor. Did the individual participate in the program?

Details

The data are taken form Spencer and Mazzeo (1980) who examined whether a new method of teaching economics significantly influenced performance in later economics courses.

Source

Online complements to Greene (2003).

https://pages.stern.nyu.edu/~wgreene/Text/tables/tablelist5.htm

References

Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall.

Spector, L. and Mazzeo, M. (1980). Probit Analysis and Economic Education. Journal of Economic Education, 11, 37–44.

See also

Greene2003

Examples

data("ProgramEffectiveness")

## Greene (2003), Table 21.1, col. "Probit"
fm_probit <- glm(grade ~ average + testscore + participation,
  data = ProgramEffectiveness, family = binomial(link = "probit"))
summary(fm_probit)
#> 
#> Call:
#> glm(formula = grade ~ average + testscore + participation, family = binomial(link = "probit"), 
#>     data = ProgramEffectiveness)
#> 
#> Coefficients:
#>                  Estimate Std. Error z value Pr(>|z|)   
#> (Intercept)      -7.45231    2.57152  -2.898  0.00376 **
#> average           1.62581    0.68973   2.357  0.01841 * 
#> testscore         0.05173    0.08119   0.637  0.52406   
#> participationyes  1.42633    0.58695   2.430  0.01510 * 
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> (Dispersion parameter for binomial family taken to be 1)
#> 
#>     Null deviance: 41.183  on 31  degrees of freedom
#> Residual deviance: 25.638  on 28  degrees of freedom
#> AIC: 33.638
#> 
#> Number of Fisher Scoring iterations: 6
#>