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Sr. no.
Estimator
Model 1
Model 2
Model 3
Model 4
Model fits
1
\(\chi^{2} fit \left( {df} \right)\)
168.54 (105)**
170.38 (104)***
258.26 (99)***
254.30 (97)***
2
RMSEA
.034
.036
.055
.055
3
CFI
.967
.961
.901
.901
4
TFI
.957
.949
.865
.863
Model coefficient estimator (S.E.)
1
β
x1
.88 (.04)***
.87 (.04)***
.82 (.07)***
.85 (.06)**
2
β
x2
.79 (.05)***
.76 (.06)***
.62 (.07)***
.56 (.10)***
3
β
m1
.45 (.07)***
.56 (.05)***
.39 (.04)**
.46 (.06)***
4
β
m2
.74 (.05)***
.84 (.04)***
.74 (.05)***
.76 (.04)***
5
β
y1
.89 (.08)**
.90 (.08)***
.84 (.09)***
.84 (.09)*
6
β
y2
.60 (.11)**
.64 (.12)***
.59 (.11)***
.60 (.12)***
7
a
1
.16 (.07)*
− .17 (.06)*
.32 (.08)***
− .40 (.07)***
8
b
1
− .29 (.18)*
.21 (.12), ns
.10 (.07), ns
.21 (.11), ns
9
a
2
− .23 (.08)*
.16 (.07)*
− .11 (.07), ns
.12 (.07), ns
10
b
2
− .02 (.05), ns
− .04 (.06), ns
− .31 (.12)*
− .15 (.10), ns
Indirect effect [95% bootstrap confidence intervals]
1
a
1
b
1
− .13 [− .35, − .01]
− .09 [− .24, − .002]
− .47 [− 1.01, − .13]
− .48 [− 1.03, − .04]
2
a
2
b
2
.00 [− .01, .01]
.00 [− .02, .00]
.00 [− .02, .00]
.00 [− .01, .00]
Model 1 = maternal attachment → synthesis → NSSI; Model 2 = maternal attachment → confusion → NSSI; Model 3 = peer attachment → synthesis → NSSI; Model 4 = peer attachment → confusion → NSSI
* p < .05; ** p < .01; *** p < .001
