Mplus model64latent 模型讲解

使用Mplus分析复杂调节中介模型：一个速查指南

理论模型
数学模型
代码解读
条件间接效应及图形展示

大家好，欢迎来到本教程。这份PPT将会快速带大家了解如何使用Mplus软件分析复杂的调节中介模型。我们不会深入探讨复杂的数学推导，而是聚焦于模型的搭建、Mplus代码的解读以及结果的应用。首先，我们会简要介绍一下该模型的理论模型，帮助大家理解各个变量之间的关系。然后，我们会直接展示Mplus的代码，并逐行解释代码的含义，让大家能够快速上手。重点在于理解如何使用代码来估计模型参数，以及如何计算在不同调节变量取值下的条件间接效应。最后，我们还会展示如何利用Mplus的PLOT命令绘制条件间接效应的图形，直观地展示结果。本教程的代码基于Andrew Hayes的PROCESS宏，并假设所有潜变量均由连续观测变量测量，方便大家理解和应用。如果您有任何统计方面的疑问，欢迎联系Data Sense。

理论模型

数学模型

数学公式1

Y = b0 + b1M + b2W + b3V + b4MW + b5MV + c'X
M = a0 + a1X + a2W + a3XW

数学公式2

Y = b0 + b1M + b2W + b3V + b4MW + b5MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2W + b3V + b4(a0 + a1X + a2W + a3XW)W + b5(a0 + a1X + a2W + a3XW)V + c'X

数学公式3

Y = b0 + b1M + b2W + b3V + b4MW + b5MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2W + b3V + b4(a0 + a1X + a2W + a3XW)W + b5(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2W + b3V + a0b4W + a1b4XW + a2b4WW + a3b4XWW + a0b5V + a1b5XV + a2b5WV + a3b5XWV + c'X

数学公式4

Y = b0 + b1M + b2W + b3V + b4MW + b5MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2W + b3V + b4(a0 + a1X + a2W + a3XW)W + b5(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2W + b3V + a0b4W + a1b4XW + a2b4WW + a3b4XWW + a0b5V + a1b5XV + a2b5WV + a3b5XWV + c'X
Y = (b0 + a0b1 + a2b1W + b2W + b3V + a0b4W + a2b4WW + a0b5V + a2b5WV) + (a1b1 + a3b1W + a1b4W + a3b4WW + a1b5V + a3b5WV + c')X

数学公式5

Y = b0 + b1M + b2W + b3V + b4MW + b5MV + c'X
M = a0 + a1X + a2W + a3XW
Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2W + b3V + b4(a0 + a1X + a2W + a3XW)W + b5(a0 + a1X + a2W + a3XW)V + c'X
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2W + b3V + a0b4W + a1b4XW + a2b4WW + a3b4XWW + a0b5V + a1b5XV + a2b5WV + a3b5XWV + c'X
Y = (b0 + a0b1 + a2b1W + b2W + b3V + a0b4W + a2b4WW + a0b5V + a2b5WV) + (a1b1 + a3b1W + a1b4W + a3b4WW + a1b5V + a3b5WV + c')X
X 对 Y 的间接效应 (在 W, V 条件下): (a1 + a3W)(b1 + b4W + b5V)
X 对 Y 的直接效应: c'

代码解读1

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4
Y1 Y2 Y3 Y4;

代码解读2

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;

代码解读3

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;

代码解读4

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;
MW | M XWITH W;
MV | M XWITH V;
XW | X XWITH W;

代码解读5

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;
MW | M XWITH W;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON W (b2);
Y ON V (b3);
Y ON MW (b4);
Y ON MV (b5);
Y ON X (cdash);
M ON X (a1);
M ON W (a2);
M ON XW (a3);

代码解读6

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;
MW | M XWITH W;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON W (b2);
Y ON V (b3);
Y ON MW (b4);
Y ON MV (b5);
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 + ... ;
...
TLOW_LOV = ILOW_LOV + cdash; ...

代码解读7

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;
MW | M XWITH W;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON W (b2);
Y ON V (b3);
Y ON MW (b4);
Y ON MV (b5);
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 + ... ;
...
TLOW_LOV = ILOW_LOV + cdash; ...
PLOT(PLOW_LOV PMEW_LOV PHIW_LOV ...);
LOOP(XVAL,-3,3,0.1);
PLOW_LOV = ILOW_LOV*XVAL; ...

代码解读8

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;
MW | M XWITH W;
MV | M XWITH V;
XW | X XWITH W;
Y ON M (b1);
Y ON W (b2);
Y ON V (b3);
Y ON MW (b4);
Y ON MV (b5);
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 + ... ;
...
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;

资源汇总

本视频讲义地址: https://mlln.cn/mplus-model-templates/model64latent.html
图书《MPlus中介调节模型》打包下载: 点击下载
图书《MPlus中介调节模型》在线看: 点击查看
视频教程: 点击这里打开视频
Mplus 模型模板教程列表: https://mlln.cn/mplus-model-templates
统计咨询: https://wx.zsxq.com/group/88888188828842