REGRESI DENGAN VARIABEL MEDIATOR ATAU INTERVAL ANALISIS JALUR ( PATH PATH ANALYSIS ANALYSIS )
Untuk Memenuhi Tugas Presentasi Matakuliah Analisis Multivariate Yang Yang Dibina Oleh Dr. H. Cipto Wardoo !.".# M.Pd.# M.!i.# Ak# CA.
Disusun Oleh$ %urnia &iest Utami
'()*+',)),-+ '()*+',)),- +
!atrio Wiaksono
' ( ) * + ' , )) / * 0
UNIVERSITAS NEGERI MALANG PASCASARJANA PROGRAM STUDI AKUNTANSI OKTOBER 2016
REGRESI DENGAN VARIABEL MEDIATOR AT ATAU INTERVENIN, INTERVENIN , ANALISIS JALUR (PATH (PATH ANALYSIS) ANALYSIS)
A. An!"#" An!"#"## J!$% (P&' (P&' An! An!#"# #"#)) '. Membuka Membuka !PP! !PP! ang ang dimili dimiliki ki baik baik !PP! !PP! v++ atau atau v+/
2. Pilih menu ILE # kemudian klik O*+n kemudian pilih D&.
. %emudian menari 1older Data Multivariate kemudia klik 1ile +-*!++./!#
*. 2ni merupakan tampilan data +-*!++./!#
0. Dari !P!! data editor# pilih menu Analyze, kemudia pilih R+%+##"n dan L"n+%.
(. Pada kotak D+*+n+n isikan variable 3B+"nn"n #!% (#!+"n)3 dan pada kotak In+*+n+n isikan variabel
O$&*$& P+%#-n P&' n!# !n4' 1 V%"!+# En&+%+5R+-+
4ariables "ntered
Model '
4ariables &emoved
Method
"duational . 5evel 6ears7 b
"nter
a. Dependent 4ariable$ 8eginning !alar b. All re9uested variables entered. Model !ummar Model & '
.(//a
Ad:usted & & !9uare !9uare
!td. "rror o1 the "stimate
.*)'
;(#)-,.+0-
.*))
a. Preditors$ 6Constant7# "duational 5evel 6ears7
ANOVA
!um o1 !9uares
Model '
d1
&egression ''=*=,),-'+. ' /'= &esidual
'=00/)-()0/. *=+ '/=
Total
+-/))-)*-(0. *=/ *0*
Mean !9uare <
!ig.
''=*=,),-'+. /'0.,-= /'=
.))) b
/=',,=(+.,+*
a. Dependent 4ariable$ 8eginning !alar b. Preditors$ 6Constant7# "duational 5evel 6ears7 C+77"8"+n&#
Unstandardi>ed Coe11iients Model '
8 6Constant7
!tandardi>ed Coe11iients
!td. "rror 8eta
?(+-).-(= '/*).-+)
"duational '=+=.0+, 5evel 6ears7
-=.'-=
a. Dependent 4ariable$ 8eginning !alar
B. L4$4n R+%+#" P+%#-n
.(//
t
!ig.
?*.(-+
.)))
'=.==/
.)))
H#"! $&*$& SPPS P+%#-n 4+ 2
V%"!+# En&+%+5R+-+
4ariables Model "ntered '
4ariables &emoved
Method
8eginning !alar# . "duational 5evel 6ears7 b
"nter
a. Dependent 4ariable$ Current !alar b. All re9uested variables entered.
M+! S$--%
Model
&
& !9uare
!td. "rror o1 the Ad:usted & !9uare "stimate
'
.,-)a
.=-+
.=-+
;=#=-(.0+*
a. Preditors$ 6Constant7# 8eginning !alar# "duational 5evel 6ears7 ANOVA !um o1 !9uares
Model '
d1
Mean !9uare <
!ig.
&egression ')-+,(/,-++ =./**
0*(*/'-*(*, ,-,.-*= .(=+
.))) b
&esidual
+,(/)')('/, *=' .--(
()=,0=,=.-, '
Total
'/=-'(*-0*/ *=/ (./*)
a. Dependent 4ariable$ Current !alar b. Preditors$ 6Constant7# 8eginning !alar# "duational 5evel 6ears7
C+77"8"+n&#
Model
Unstandardi>ed Coe11iients
!tandardi>ed t Coe11iients
!ig.
'
8
!td. "rror
6Constant7
?=,),.='*
'=0/.,()
"duational 5evel 6ears7
')+)./-)
'().00)
8eginning !alar
'.(=/
.)0-
8eta ?*.*0+
.)))
.'=+
(./0(
.)))
.=='
+,.*+/
.)))
a. Dependent 4ariable$ Current !alar B. S+! T+#& n B&#%**"n 1. 8uku pada menu "!+ kemudian klik O*+n 9: D&, buka 1ile +-*!++./!#
2. Dari menu utama !P!! pilih menu O*+n kemudian Script , buka Script aitu S+!;#*##.##
. %lik O*+n , akan tampak
tampilan sript di ba@ah ini
<. Pilih Macro lalu Run. Akan
tampilan seperti di ba@ah ini
0. Pada kotak "+*+n+n %"!+ (=) isikan 3E$83# pada kotak 3P%*#+
-+"&% (M) isikan !albegin# Pada kotak S+! &+#& S&n%& E%%
isikan !eond order# dan pada B&#&%* sampel isikan '))) kemudia klik O4
(. Hasil output S+! &+#& dan B&#&%* Run MATRIX procedure: Error # 34 in column 20. Text: bootstrp.sa !"!! !tatistics cannot access a ile $it% t%e &ien ile speciication. T%e
ile speciication is eit%er s'ntacticall' inalid( speciies an inalid drie( speciies a protected director'( speciies a protected ile( or speciies a non)s%arable ile. Execution o t%is command stops. ************************************************************ ************* "reac%er And +a'es ,2004- !"!! !cript or !imple Mediation /ritten b' Andre$ . +a'es( T%e %io !tate 1niersit' %ttp:$$$.comm.o%io)state.edua%a'es ARIA5E! 8 X M
I6 !IM"5E ME7IATI6 M7E5 salar' educ salbe&in
7E!9RI"TIE! !TATI!TI9! A67 "EAR!6 9RRE5ATI6! Mean !7 salar' educ salar' 344;.<=> ?0?<.== .0000 .==0= educ 3.4;= 2.>>4> .==0= .0000 salbe&in ?0=.0>= ?>?0.=3>2 .>>0 .=332
salbe&in .>>0 .=332 .0000
!AM"5E !I@E 4?4 7IRE9T And TTA5 EE9T! 9oe s.e. b,8X3;0;.;0=? 204.<4?0 b,MX?2?.<2>3 ;?.;=; b,8M.X.=?2= .0<>> b,8X.M- 020.3;0 =0.<<04
t ;.<0 ?.??3< 2>.4234 =.3<<=
!i&,t$o.0000 .0000 .0000 .0000
I67IRE9T EE9T And !I6II9A69E 1!I6 6RMA5 7I!TRI1TI6 alue s.e. 55 ;< 9I 15 ;< 9I @ !i&,t$oEect 2>>;.<== ;.>2?; 2<3.<340 32=<.4;;2 <.0=3 .0000 T!TRA" RE!15T! or I67IRE9T EE9T 7ata Mean s.e. 55 ;< 9I 15 ;< 9I ;; 9I 15 ;; 9I Eect 2>>;.<== 2>;;.=4;0 22?.23=> 24<;.2>0? 33=3.>?= 233>.=>;3 3<02.400 61MER T!TRA" RE!AM"5E! 000 AIR9+I57 ET A5. ,200;- ARIA69E I6 8 A9916TE7 R 8 I67IRE9T EE9T: .4>< ********************************* 6TE! **********************************
55
)))))) E67 MATRIX )))))
C. Cn&' An!"#"# J!$% L+"' K-*!+4
'. 8uka
+. Dari !P!! data editor# pilih menu Analyze, kemudia pilih R+%+##"n dan L"n+%
/. Pada kotak D+*+n+n isikan variable $&n- dan pada kotak In+*+n+n isikan variable + . %emudian klik O4
*. Tampilan ouput !P!! persamaan regresi 6'7 Model Summaryb
Model 1
R
Adjusted R
Std. Error of the
Square
Estimate
R Square
.268a
.072
.058
2.697
a. Preditors! "#o$sta$t%& a'e (. )e*e$de$t +aria(le! auto$om
ANOVAa Model 1
Sum of Squares Re'ressio$
df
Mea$ Square
-8.259
1
-8.259
Residual
9.726
68
7.275
/otal
5-2.986
69
a. )e*e$de$t +aria(le! auto$om (. Preditors! "#o$sta$t%& a'e
, 5.259
Si'. .025(
Coefficientsa Residuals Statisticsa Model $sta$dardied #oeffiie$ts Sta$dardied t Mi$imum Ma3imum Mea$ Std. )e4iatio$ #oeffiie$ts Predited +alue 7.22 10.80 9.1 .75 Std. Error eta Residual .298 5.768 .000 2.678 1 "#o$sta$t% 7.218 1.011 7.11 Std. Predited +alue 2.950 1.861 .000 1.000 a'e .057 .025 .268 2.29Std. Residual 1.592.1-9 .000 .99a. )e*e$de$t +aria(le! auto$om a. )e*e$de$t +aria(le! auto$om
Si'. 70 70 70 70
.000 .025
0. 5akukan regresi persamaan 6+7 dengan mengganti pada kontak D+*+n+n isikan variable #&"# dan pada kotak In+*+n+n isikan variable $&ndan "n8-+
(. Hasil output !P!! persamaan 6+7 Model Summaryb
Model 1
R
Adjusted R
Std. Error of the
Square
Estimate
R Square
.110a
.012
.017
2.075
a. Preditors! "#o$sta$t%& i$ome& auto$om (. )e*e$de$t +aria(le! satis
ANOVAa Model 1
Sum of Squares Re'ressio$
df
Mea$ Square
-.52-
2
1.762
Residual
288.19
67
.-05
/otal
291.9-
69
a. )e*e$de$t +aria(le! satis (. Preditors! "#o$sta$t%& i$ome& auto$om
,
Si'. .09
.666(
Coefficientsa Sta$dardied $sta$dardied #oeffiie$ts Model
1
"#o$sta$t%
#oeffiie$ts
Std. Error
eta
12.67
1.297
auto$om
.05
.09
i$ome
.000
.000
t
Si'.
9.61
.000
.060
.75
.6-6
.111
.875
.-85
a. )e*e$de$t +aria(le! satis
Residuals Statisticsa Mi$imum Predited +alue
Ma3imum
Mea$
Std. )e4iatio$
11.-
12.96
11.8-
.226
70
Residual
6.762
5.187
.000
2.05
70
Std. Predited +alue
1.751
5.001
.000
1.000
70
Std. Residual
-.259
2.500
.000
.985
70
a.
)e*e$de$t +aria(le! satis
=. 5akukan regresi persamaan 6/7 dengan mengganti pada kontak D+*+n+n isikan variable In8-+ dan pada kotak In+*++n isikan variable + dan $&n-.
,. Hasil Output persamaan /
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.8-a
1
Adjusted R
.2--
.210
157.189
a. Preditors! "#o$sta$t%& auto$om& a'e (. )e*e$de$t +aria(le! i$ome
ANOVAa Model 1
Sum of Squares Re'ressio$
df
Mea$ Square
,
-209-.989
2
2162067.9
Residual
12267779.297
67
212--99.691
/otal
18550871.286
69
Si'. .000(
10.182
a. )e*e$de$t +aria(le! i$ome (. Preditors! "#o$sta$t%& auto$om& a'e
Coefficientsa Sta$dardied $sta$dardied #oeffiie$ts Model 1
"#o$sta$t%
Std. Error
eta
6-.5-1
722.-20
9.877
1-.906
109.888
65.51
a'e auto$om
#oeffiie$ts t
Si'.
6.16
.000
.-98
-.587
.001
.186
1.677
.098
a. )e*e$de$t +aria(le! i$ome
Residuals Statisticsa Mi$imum Predited +alue
Ma3imum
Mea$
Std. )e4iatio$
551-.6-
90-6.20
7595.71
791.6-1
70
7987.998
2282.-9
.000
1-5.915
70
Std. Predited +alue
2.6-0
1.820
.000
1.000
70
Std. Residual
5.82
1.566
.000
.985
70
Residual
a. )e*e$de$t +aria(le! i$ome
D. R+%+#" +nn M$!&"*!+ M+"&%
1. >8uka
2.
3.
4. Run MATRIX procedure: 7ependent( Independent( and "roposed Mediator ariables: 7 B I69ME I B EAR6! ME7! B /EA5T+ !AI6 !tatistical 9ontrols: 96TR5B !I@E AE !ample siCe 00 I to Mediators ,a pat%s9oe se /EA5T+ .;;0 .23? !AI6 .3>>< .0?=;
t >.3;?< <.0<=
p .0000 .0000
7irect Eects o Mediators on 7 ,b pat%s9oe se t
p
/EA5T+ !AI6
.033< .0<;
.0;> .0=
.=;00 .2<;?
Total Eect o I on 7 ,c pat%9oe se t EAR6! .;<2> .04=0 20.?2;;
.0;43 .?;
p .0000
7irect Eect o I on 7 ,c)prime pat%9oe se t p EAR6! .>>00 .0==4 3.243> .0000 "artial Eect o 9ontrol ariables on 7 9oe se t p !I@E ).24? .== ).32>; .>? AE .;4 .03<3 3.3?>> .00 Model !ummar' or 7 Model R)sD Ad R)sD .>34< .>2
d <.0000
d2 ;4.0000
p .0000
Error # 34 in column 2. Text: indirect.sa !"!! !tatistics cannot access a ile $it% t%e &ien ile speciication. T%e ile speciication is eit%er s'ntacticall' inalid( speciies an inalid drie( speciies a protected director'( speciies a protected ile( or speciies a non)s%arable ile. Execution o t%is command stops. ************************************************************ ***** T!TRA" RE!15T! R I67IRE9T EE9T! Indirect Eects o I on 7 t%rou&% "roposed Mediators ,ab pat%s7ata boot ias !E TTA5 .0?2> .0?=2 .0033 .0<=? /EA5T+ .0==? .0=;; .0033 .0=4 !AI6 .00=2 .00=2 .0000 .02=? 9 .0=0< .0=3? .0032 .0?<> ias 9orrected and Accelerated 9onidence Interals 5o$er 1pper TTA5 ).00?> .220> /EA5T+ ).00>= .2?=0 !AI6 ).0<>4 .0<<< 9 ).03 .2;;; ************************************************************ *****
5eel o 9onidence or 9onidence Interals: ;<
6umber o ootstrap Resamples: 000 ************************************************************ ***** I67IRE9T EE9T contrast 7EI6ITI6!: IndFE MI61! IndFE2
contrast 9
IndEF /EA5T+
IndEF2 !AI6
)))))) E67 MATRIX )))))
