SPSS juga bisa melakukan uji regresi
data panel. Hanya saja terbatas yang bisa diuji model pool/common dan
model fix baik dengan time series yang tetap atau efek cross section
yang tetap
Untuk Model Pool
Analyze > Regression > Linier Regression
Pada Dependen : Select variabel NP
Pada variabel Independen: select variabel UK, K_Und, K_Ind
Klik Ok
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
,590a
|
,348
|
,255
|
1,27811
|
|
a. Predictors: (Constant), K_Aud, K_Ind, UK
|
||||
|
ANOVAa
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
18,299
|
3
|
6,100
|
3,734
|
,027b
|
|
Residual
|
34,305
|
21
|
1,634
|
|||
|
Total
|
52,604
|
24
|
||||
|
a. Dependent Variable: NP
|
||||||
|
b. Predictors: (Constant), K_Aud, K_Ind, UK
|
||||||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
-6,135
|
3,379
|
-1,816
|
,084
|
|
|
UK
|
,095
|
,184
|
,183
|
,514
|
,612
|
|
|
K_Ind
|
12,932
|
3,884
|
,714
|
3,330
|
,003
|
|
|
K_Aud
|
2,808
|
2,214
|
,494
|
1,268
|
,219
|
|
|
a. Dependent Variable: NP
|
||||||
Untuk Model Fix
- Model slope tetap, intersept berbeda antar individu (A,B,C,D,E)
Buat variabel dummy, sebanyak jumlah individu/cross section
Analyze > Regression > Linier Regression
Pada Dependen : Select variabel NP
Pada variabel Independen: select variabel UK, K_Und, K_Ind, A, B, C, D,E
Klik Ok
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
,590a
|
,348
|
,255
|
1,27811
|
|
a. Predictors: (Constant), K_Aud, K_Ind, UK
|
||||
|
ANOVAa
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
28,158
|
7
|
4,023
|
2,797
|
,039b
|
|
Residual
|
24,446
|
17
|
1,438
|
|||
|
Total
|
52,604
|
24
|
||||
|
a. Dependent Variable: NP
|
||||||
|
b. Predictors: (Constant), E, D, C, K_Ind, A, K_Aud, UK
|
||||||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
-4,022
|
10,370
|
-,388
|
,703
|
|
|
UK
|
,745
|
1,518
|
1,437
|
,491
|
,630
|
|
|
K_Ind
|
2,096
|
16,377
|
,116
|
,128
|
,900
|
|
|
K_Aud
|
1,878
|
4,150
|
,330
|
,453
|
,657
|
|
|
A
|
2,069
|
4,321
|
,571
|
,479
|
,638
|
|
|
C
|
-,667
|
4,484
|
-,184
|
-,149
|
,884
|
|
|
D
|
-,033
|
,820
|
-,009
|
-,041
|
,968
|
|
|
E
|
-3,905
|
13,484
|
-1,077
|
-,290
|
,776
|
|
|
a. Dependent Variable: NP
|
||||||
- Model slope tetap, intersept berbeda antar waktu
Buat variabel dummy, sebanyak jumlah time series
Analyze > Regression > Linier Regression
Pada Dependen : Select variabel NP
Pada variabel Independen: select variabel UK, K_Und, K_Ind, T1,T2,T3,T4,T5
Klik Ok
|
Model Summary
|
||||
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
,841a
|
,707
|
,587
|
,95179
|
|
a. Predictors: (Constant), T5, UK, T4, T2, K_Ind, T3, K_Aud
|
||||
|
ANOVAa
|
||||||
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
1
|
Regression
|
37,204
|
7
|
5,315
|
5,867
|
,001b
|
|
Residual
|
15,400
|
17
|
,906
|
|||
|
Total
|
52,604
|
24
|
||||
|
a. Dependent Variable: NP
|
||||||
|
b. Predictors: (Constant), T5, UK, T4, T2, K_Ind, T3, K_Aud
|
||||||
|
Coefficientsa
|
||||||
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
||
|
B
|
Std. Error
|
Beta
|
||||
|
1
|
(Constant)
|
-7,389
|
2,564
|
-2,882
|
,010
|
|
|
UK
|
,022
|
,142
|
,042
|
,153
|
,880
|
|
|
K_Ind
|
14,879
|
2,932
|
,822
|
5,075
|
,000
|
|
|
K_Aud
|
2,358
|
1,709
|
,414
|
1,380
|
,186
|
|
|
T2
|
,394
|
,606
|
,109
|
,650
|
,524
|
|
|
T3
|
1,325
|
,628
|
,365
|
2,110
|
,050
|
|
|
T4
|
1,935
|
,612
|
,533
|
3,160
|
,006
|
|
|
T5
|
2,339
|
,609
|
,645
|
3,844
|
,001
|
|
|
a. Dependent Variable: NP
|
||||||
Hanya saja yang sering diuji adalah dalam model fix ialah model dengan fix efek, intersep berbeda antar individu
Untuk menguji anatara model pool dan
fix, dapat dilihat dari nilai r-square adjusted yang terbesar dan
banyaknya variabel independen yang signifikan.
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