1. Run a Crosstab of the variables X1 Individualized Education Plan (X1IEPFLAG) and IEP (5).
## 
##  
##    Cell Contents
## |-------------------------|
## |                       N |
## | Chi-square contribution |
## |           N / Row Total |
## |           N / Col Total |
## |         N / Table Total |
## |-------------------------|
## 
##  
## Total Observations in Table:  236 
## 
##  
##              | df$IEP 
## df$X1IEPFLAG |         0 |         1 | Row Total | 
## -------------|-----------|-----------|-----------|
##            1 |       191 |         0 |       191 | 
##              |     8.581 |    36.419 |           | 
##              |     1.000 |     0.000 |     0.809 | 
##              |     1.000 |     0.000 |           | 
##              |     0.809 |     0.000 |           | 
## -------------|-----------|-----------|-----------|
##            2 |         0 |        45 |        45 | 
##              |    36.419 |   154.581 |           | 
##              |     0.000 |     1.000 |     0.191 | 
##              |     0.000 |     1.000 |           | 
##              |     0.000 |     0.191 |           | 
## -------------|-----------|-----------|-----------|
## Column Total |       191 |        45 |       236 | 
##              |     0.809 |     0.191 |           | 
## -------------|-----------|-----------|-----------|
## 
##

 

  1. What percentage of cases are students who have an IEP, or individualized education plan, and what values for IEP are assigned to students with missing information in the X1IEPFLAG variable? (5)

19% of students in the datset. According to the codebook, students with missing information in the X1IEPFLAG variable have the value -9.

 

  1. Run a regression that meets these criteria (5):
  1. Independent Variable – IEP
  2. Dependent Variable - X3 Total credits earned (X3TCREDTOT)
term estimate std.error statistic p.value
(Intercept) 24.2162921 0.547455 44.2343024 0.00000
IEP -0.9601946 1.265257 -0.7588932 0.44874

 

  1. Provide a narrative interpretation of the coefficient on the independent variable and the y-intercept value (5)

Because p = .45, we cannot conclude if IEP is a significant indicator for X3 Total Credits earned.

 

  1. Run a regression that meets these criteria (5):
  1. Independent Variable – IEP
  2. Independent Variable – X1SES
  3. Dependent Variable - X3 Total credits earned ()
term estimate std.error statistic p.value
(Intercept) 23.8556061 0.5544746 43.0238024 0.0000000
IEP 0.8015432 1.3668835 0.5864019 0.5582836
X1SES 2.2321304 0.6390304 3.4929956 0.0005909

 

  1. Provide a narrative interpretation of the all of the coefficients from model 5. (5)

X3 Total Credits Earned was regressed on IEP and X1SES (Socioeconomic Status). X1SES was found to have a significant relationship with the dependent variable (p < 0.001) where as X1SES rises by one unit, total credits earned increases by 2.23 points, holding the IEP variable constant. However, the IEP was not found to have a significant relationship with the dependent variable holding X1SES constant (p = .56). The intercept (y = 23.86) is the number of credits someone would be predicted to have if they had no IEP and their X1SES was also 0.

 

 

 

 

  1. Generate one set of output which compares two models to assess whether a complete model performs better than a reduced form model based on the change in R2 values. (10)
  1. The complete model regresses X3 GPA for all academic courses (X3TGPAACAD) on X1 Socio-economic status composite (X1SES), X2 Mathematics standardized theta score (X1TXMSCOR), and IEP status.
  2. The reduced model regresses X3 GPA for all academic courses (X3TGPAACAD) on X1 Socio-economic status composite (X1SES) and X2 Mathematics standardized theta score (X2TXMTSCOR) only.
Model 1 Model 2
(Intercept) 0.300 0.327
(0.324) (0.325)
X1SES 0.098 0.082
(0.076) (0.078)
X2TXMTSCOR 0.044 0.044
(0.006) (0.006)
IEP -0.136
(0.144)
Num.Obs. 175 175
R2 0.325 0.328
R2 Adj. 0.317 0.317
AIC 378.7 379.8
BIC 391.3 395.6
Log.Lik. -185.333 -184.876
F 41.380 27.868
Res.Df RSS Df Sum of Sq F Pr(>F)
172 85.19947 NA NA NA NA
171 84.75633 1 0.4431426 0.8940618 0.3457131
  1. Provide a narrative interpretation of the Model Summary table generated in question 7. (10)