来自图书《MPlus中介调节模型》
Y = b0 + b1M + b2V + b3MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2V + b3(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2V + a0b3V + a1b3XV + a2b3VW + a3b3XWV + c'X
Y = (b0 + a0b1 + a2b1W + b2V + a0b3V + a2b3VW) + (a1b1 + a3b1W + a1b3V + a3b3WV + c')X
Y = b0 + b1M + b2V + b3MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2V + b3(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2V + a0b3V + a1b3XV + a2b3VW + a3b3XWV + c'X
Y = (b0 + a0b1 + a2b1W + b2V + a0b3V + a2b3VW) + (a1b1 + a3b1W + a1b3V + a3b3WV + c')X
X 对 Y 的间接效应(在 W,V 条件下):(a1 + a3W)(b1 + b3V)
Y = b0 + b1M + b2V + b3MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2V + b3(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2V + a0b3V + a1b3XV + a2b3VW + a3b3XWV + c'X
Y = (b0 + a0b1 + a2b1W + b2V + a0b3V + a2b3VW) + (a1b1 + a3b1W + a1b3V + a3b3WV + c')X
X 对 Y 的间接效应(在 W,V 条件下):(a1 + a3W)(b1 + b3V)
X 对 Y 的直接效应:c'
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;
ANALYSIS:
TYPE = GENERAL RANDOM;
ESTIMATOR = ML;
ALGORITHM = INTEGRATION;
MODEL:
X BY X1 X2 X3 X4;
M BY M1 M2 M3 M4;
W BY W1* W2 W3 W4;
V BY V1* V2 V3 V4;
Y BY Y1 Y2 Y3 Y4;
W@1; V@1;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON V (b2);
Y ON MV (b3);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;
ANALYSIS:
TYPE = GENERAL RANDOM;
ESTIMATOR = ML;
ALGORITHM = INTEGRATION;
MODEL:
X BY X1 X2 X3 X4;
M BY M1 M2 M3 M4;
W BY W1* W2 W3 W4;
V BY V1* V2 V3 V4;
Y BY Y1 Y2 Y3 Y4;
W@1; V@1;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON V (b2);
Y ON MV (b3);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);
MODEL CONSTRAINT:
NEW(LOW_W MED_W HIGH_W LOW_V MED_V HIGH_V ...);
LOW_W = -1; ... HIGH_V = 1;
ILOW_LOV = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V; ...
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;
ANALYSIS:
TYPE = GENERAL RANDOM;
ESTIMATOR = ML;
ALGORITHM = INTEGRATION;
MODEL:
X BY X1 X2 X3 X4;
M BY M1 M2 M3 M4;
W BY W1* W2 W3 W4;
V BY V1* V2 V3 V4;
Y BY Y1 Y2 Y3 Y4;
W@1; V@1;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON V (b2);
Y ON MV (b3);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);
MODEL CONSTRAINT:
NEW(LOW_W MED_W HIGH_W LOW_V MED_V HIGH_V ...);
LOW_W = -1; ... HIGH_V = 1;
ILOW_LOV = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V; ...
TLOW_LOV = ILOW_LOV + cdash; ...
PLOT(PLOW_LOV PMEW_LOV PHIW_LOV ...);
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;
ANALYSIS:
TYPE = GENERAL RANDOM;
ESTIMATOR = ML;
ALGORITHM = INTEGRATION;
MODEL:
X BY X1 X2 X3 X4;
M BY M1 M2 M3 M4;
W BY W1* W2 W3 W4;
V BY V1* V2 V3 V4;
Y BY Y1 Y2 Y3 Y4;
W@1; V@1;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON V (b2);
Y ON MV (b3);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);
MODEL CONSTRAINT:
NEW(LOW_W MED_W HIGH_W LOW_V MED_V HIGH_V ...);
LOW_W = -1; ... HIGH_V = 1;
ILOW_LOV = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V; ...
TLOW_LOV = ILOW_LOV + cdash; ...
PLOT(PLOW_LOV PMEW_LOV PHIW_LOV ...);
LOOP(XVAL,-3,3,0.1);
PLOW_LOV = ILOW_LOV*XVAL; ...
PLOT: TYPE = plot2;
USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;
ANALYSIS:
TYPE = GENERAL RANDOM;
ESTIMATOR = ML;
ALGORITHM = INTEGRATION;
MODEL:
X BY X1 X2 X3 X4;
M BY M1 M2 M3 M4;
W BY W1* W2 W3 W4;
V BY V1* V2 V3 V4;
Y BY Y1 Y2 Y3 Y4;
W@1; V@1;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON V (b2);
Y ON MV (b3);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);
MODEL CONSTRAINT:
NEW(LOW_W MED_W HIGH_W LOW_V MED_V HIGH_V ...);
LOW_W = -1; ... HIGH_V = 1;
ILOW_LOV = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V; ...
TLOW_LOV = ILOW_LOV + cdash; ...
PLOT(PLOW_LOV PMEW_LOV PHIW_LOV ...);
LOOP(XVAL,-3,3,0.1);
PLOW_LOV = ILOW_LOV*XVAL; ...
PLOT: TYPE = plot2;
OUTPUT: CINT;