Mplus model44latent 模型讲解

来自图书《MPlus中介调节模型》

复杂潜变量模型(包含中介、调节和调节中介效应)的Mplus分析教程

• 理论模型
• 数学模型
• 数学推导
• 代码解读

大家好，欢迎来到本教程。本教程将带大家学习如何用Mplus构建并分析一个非常复杂的潜变量模型，这个模型包含中介效应、调节效应，以及两者结合的调节中介效应。 我们将会一步步地讲解，即使你对Mplus不那么熟悉，也能轻松上手。

首先，我们会介绍模型的理论基础，也就是这个模型究竟要研究什么问题，以及它背后的逻辑。然后，我们会用数学公式来表达这个模型，清晰地展现各个变量之间的关系。 接下来，我们会对这些数学公式进行详细的推导，帮助大家理解模型的运作机制。最后，也是最重要的部分，我们会对Mplus代码进行逐行解读，讲解每一行代码的作用，以及如何修改代码来适应你自己的数据。 通过学习本教程，你将能够轻松构建和分析此类复杂模型，并且能够更深入地理解中介、调节以及调节中介效应在实证研究中的应用。 准备好了吗？让我们开始吧！

理论模型

我们来看，这个图展示了一个比较复杂的模型。在这个模型中，X会直接影响M和Y。同时，X对M的影响还会受到W的调节，X对Y的直接影响也会受到W和V的调节。M会影响Y，并且M对Y的影响会受到V和Q共同的调节，而且V和Q之间还存在相互作用。另外，V还会直接影响Y。这个图用箭头表示了变量之间的关系，箭头方向表示影响的方向。

数学模型

这张图展示了一个比较复杂的模型，它研究的是变量之间的相互影响关系。我们来看一下，这里面有几个主要的角色：X，W，V，Q，M，还有Y。

X、W、V、Q就像我们研究中的自变量，它们各自有自己的作用方式。X可以通过a1、a2、a3三个箭头影响M；M呢，它可以看作是一个中介，它通过b1这个箭头影响着Y。此外，X也可以通过c1’ 直接影响Y，而W也可以通过c2’ 直接影响Y。而X和W之间的交互作用，也会通过c3’影响Y。然后，我们看到V直接通过c4’影响Y，V和X的交互作用通过c5’影响Y。

接着，Q直接通过b2影响Y。M和V之间会产生交互作用，通过b3影响Y。M和Q之间也会产生交互作用，通过b4影响Y。V和Q之间也会产生交互作用，通过b5影响Y。最后，M、V和Q三者之间共同的交互作用，也会通过b6影响Y。

所以，这个图展示的是这些变量之间如何相互影响，包括直接的影响，通过中间变量的影响，以及变量之间相互作用的影响。

数学公式1

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW

首先，我们来看模型的基本方程式。Y是因变量，M是中介变量，Q、V、W是调节变量，X是自变量。第一个公式描述了Y如何被M、Q、V、W以及它们的交互作用所影响，同时X也有直接效应。第二个公式描述了中介变量M如何被X、W以及它们的交互作用所影响。

数学公式2

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW
将M的表达式代入Y的表达式中:

Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2Q + b3(a0 + a1X + a2W + a3XW)V + b4(a0 + a1X + a2W + a3XW)Q + b5VQ + b6(a0 + a1X + a2W + a3XW)VQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

接下来，我们将第二个公式中M的表达式代入第一个公式中。这步的目的是将Y的表达式完全用自变量X和调节变量Q、V、W表示。

数学公式3

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW
将M的表达式代入Y的表达式中:

Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2Q + b3(a0 + a1X + a2W + a3XW)V + b4(a0 + a1X + a2W + a3XW)Q + b5VQ + b6(a0 + a1X + a2W + a3XW)VQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
展开括号:

Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2Q + a0b3V + a1b3XV + a2b3WV + a3b3XWV + a0b4Q + a1b4XQ + a2b4WQ + a3b4XWQ + b5VQ + a0b6VQ + a1b6XVQ + a2b6WVQ + a3b6XWVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

现在，我们展开所有的括号，得到一个更加复杂的表达式。这个表达式展示了所有变量之间的交互效应和直接效应。

数学公式4

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW
将M的表达式代入Y的表达式中:

Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2Q + b3(a0 + a1X + a2W + a3XW)V + b4(a0 + a1X + a2W + a3XW)Q + b5VQ + b6(a0 + a1X + a2W + a3XW)VQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
展开括号:

Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2Q + a0b3V + a1b3XV + a2b3WV + a3b3XWV + a0b4Q + a1b4XQ + a2b4WQ + a3b4XWQ + b5VQ + a0b6VQ + a1b6XVQ + a2b6WVQ + a3b6XWVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
整理成`Y = a + bX`的形式:

Y = (b0 + a0b1 + a2b1W + b2Q + a0b3V + a2b3WV + a0b4Q + a2b4WQ + b5VQ + a0b6VQ + a2b6WVQ + c2'W + c4'V) + (a1b1 + a3b1W + a1b3V + a3b3WV + a1b4Q + a3b4WQ + a1b6VQ + a3b6WVQ + c1' + c3'W + c5'V)X

为了更好地分析，我们将Y的表达式整理成Y = a + bX的形式，其中a代表截距，b代表斜率。这里，a是括号内的不包含X的项的总和，b是括号内X的系数。

数学公式5

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW
将M的表达式代入Y的表达式中:

Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2Q + b3(a0 + a1X + a2W + a3XW)V + b4(a0 + a1X + a2W + a3XW)Q + b5VQ + b6(a0 + a1X + a2W + a3XW)VQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
展开括号:

Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2Q + a0b3V + a1b3XV + a2b3WV + a3b3XWV + a0b4Q + a1b4XQ + a2b4WQ + a3b4XWQ + b5VQ + a0b6VQ + a1b6XVQ + a2b6WVQ + a3b6XWVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
整理成`Y = a + bX`的形式:

Y = (b0 + a0b1 + a2b1W + b2Q + a0b3V + a2b3WV + a0b4Q + a2b4WQ + b5VQ + a0b6VQ + a2b6WVQ + c2'W + c4'V) + (a1b1 + a3b1W + a1b3V + a3b3WV + a1b4Q + a3b4WQ + a1b6VQ + a3b6WVQ + c1' + c3'W + c5'V)X
X对Y的一个间接效应（在W, V, Q的条件下）:

a1b1 + a3b1W + a1b3V + a3b3WV + a1b4Q + a3b4WQ + a1b6VQ + a3b6WVQ = (a1 + a3W)(b1 + b3V + b4Q + b6VQ)

现在，我们提取X的系数，这部分代表X对Y的间接效应，它受到调节变量W、V和Q的影响。我们可以将它进一步简化为(a1 + a3W)(b1 + b3V + b4Q + b6VQ)的形式。

数学公式6

模型方程式:

Y = b0 + b1M + b2Q + b3MV + b4MQ + b5VQ + b6MVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV

M = a0 + a1X + a2W + a3XW
将M的表达式代入Y的表达式中:

Y = b0 + b1(a0 + a1X + a2W + a3XW) + b2Q + b3(a0 + a1X + a2W + a3XW)V + b4(a0 + a1X + a2W + a3XW)Q + b5VQ + b6(a0 + a1X + a2W + a3XW)VQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
展开括号:

Y = b0 + a0b1 + a1b1X + a2b1W + a3b1XW + b2Q + a0b3V + a1b3XV + a2b3WV + a3b3XWV + a0b4Q + a1b4XQ + a2b4WQ + a3b4XWQ + b5VQ + a0b6VQ + a1b6XVQ + a2b6WVQ + a3b6XWVQ + c1'X + c2'W + c3'XW + c4'V + c5'XV
整理成`Y = a + bX`的形式:

Y = (b0 + a0b1 + a2b1W + b2Q + a0b3V + a2b3WV + a0b4Q + a2b4WQ + b5VQ + a0b6VQ + a2b6WVQ + c2'W + c4'V) + (a1b1 + a3b1W + a1b3V + a3b3WV + a1b4Q + a3b4WQ + a1b6VQ + a3b6WVQ + c1' + c3'W + c5'V)X
X对Y的一个间接效应（在W, V, Q的条件下）:

a1b1 + a3b1W + a1b3V + a3b3WV + a1b4Q + a3b4WQ + a1b6VQ + a3b6WVQ = (a1 + a3W)(b1 + b3V + b4Q + b6VQ)
X对Y的一个直接效应（在W, V的条件下）:

c1' + c3'W + c5'V

最后，我们来看X对Y的直接效应，即在控制了其他变量后，X对Y的直接影响，这部分表示为c1’ + c3’W + c5’V。它受到调节变量W和V的影响。

代码解读1

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
Y1 Y2 Y3 Y4;

第一步，我们定义分析中要用到的变量。这里X1到X4是用来测量潜变量X的，M1到M4是测量潜变量M的，以此类推，W1到W4测量潜变量W，V1到V4测量潜变量V，Q1到Q4测量潜变量Q，Y1到Y4测量潜变量Y。

代码解读2

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
Y1 Y2 Y3 Y4;
ANALYSIS:
 TYPE = GENERAL RANDOM;
 ESTIMATOR = ML;
 ALGORITHM = INTEGRATION;

第二步，我们设定分析的类型。TYPE设置为GENERAL RANDOM，表示这是一个一般随机效应模型。ESTIMATOR设置为ML，表示使用最大似然法进行参数估计。ALGORITHM设置为INTEGRATION，表示使用积分算法来处理模型中的潜变量。

代码解读3

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;

第三步，我们开始定义模型。X BY X1 X2 X3 X4表示潜变量X由X1到X4测量，其余的M, W, V, Q和Y的定义类似。注意W1，V1和Q1后面都加了星号，表示它们对应的载荷被固定为1，用来标准化对应的潜变量的方差，然后我们再固定W, V, Q的方差为1。

代码解读4

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;

第四步，我们定义潜变量的交互项。比如，MV | M XWITH V 表示创建M和V的交互项MV，其他类似。这些交互项会在后续的模型中被用到。

代码解读5

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);

第五步，我们定义Y的回归方程。例如，Y ON M (b1) 表示Y对M的回归系数是b1，类似地，我们定义了Y与其他潜变量以及交互项的关系。cdash开头的系数是直接效应。

代码解读6

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
M ON X (a1);
 M ON W (a2);
 M ON XW (a3);

第六步，我们定义M的回归方程。M受到X，W和X与W交互项的影响，对应的回归系数分别是a1，a2和a3。

代码解读7

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);

第七步，我们开始定义模型约束。首先用NEW定义一系列新的参数，包括调节变量的低、中、高水平值，以及各种条件间接效应，直接效应和总效应。

代码解读8

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;

第八步，我们定义调节变量W, V和Q的低、中、高水平的值，这里分别设置为-1，0和1，通常表示标准差的倍数。

代码解读9

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...

第九步，我们计算在不同调节变量水平组合下的条件间接效应。比如ILWLVLQ 表示W，V，Q都取低值时的间接效应，其他类似。这些公式都是根据我们之前定义的模型推导出来的，用于计算特定条件下的间接效应大小。

代码解读10

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;

第十步，我们计算不同调节变量水平组合下的直接效应。例如，DLOW_LOV 表示W和V都取低值时的直接效应。这些直接效应的计算基于之前定义的回归系数。

代码解读11

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;
TLWLVLQ = ILWLVLQ + DLOW_LOV;
TMWLVLQ = IMWLVLQ + DMEW_LOV;
THWLVLQ = IHWLVLQ + DHIW_LOV;
TLWMVLQ = ILWMVLQ + DLOW_MEV;
TMWMVLQ = IMWMVLQ + DMEW_MEV;
THWMVLQ = IHWMVLQ + DHIW_MEV;
TLWHVLQ = ILWHVLQ + DLOW_HIV;
TMWHVLQ = IMWHVLQ + DMEW_HIV;
THWHVLQ = IHWHVLQ + DHIW_HIV;
...

第十一步，我们计算不同调节变量水平组合下的总效应，总效应等于间接效应加上直接效应。例如，TLWLVLQ 等于ILWLVLQ 加 DLOW_LOV。

代码解读12

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;
TLWLVLQ = ILWLVLQ + DLOW_LOV;
TMWLVLQ = IMWLVLQ + DMEW_LOV;
THWLVLQ = IHWLVLQ + DHIW_LOV;
TLWMVLQ = ILWMVLQ + DLOW_MEV;
TMWMVLQ = IMWMVLQ + DMEW_MEV;
THWMVLQ = IHWMVLQ + DHIW_MEV;
TLWHVLQ = ILWHVLQ + DLOW_HIV;
TMWHVLQ = IMWHVLQ + DMEW_HIV;
THWHVLQ = IHWHVLQ + DHIW_HIV;
...
PLOT(PLWLVLQ PMWLVLQ PHWLVLQ PLWMVLQ PMWMVLQ PHWMVLQ
PLWHVLQ PMWHVLQ PHWHVLQ
PLWLVMQ PMWLVMQ PHWLVMQ PLWMVMQ PMWMVMQ PHWMVMQ
PLWHVMQ PMWHVMQ PHWHVMQ
PLWLVHQ PMWLVHQ PHWLVHQ PLWMVHQ PMWMVHQ PHWMVHQ
PLWHVHQ PMWHVHQ PHWHVHQ);

第十二步，我们定义要绘制的图。这里列出了一系列要绘制的条件间接效应。

代码解读13

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;
TLWLVLQ = ILWLVLQ + DLOW_LOV;
TMWLVLQ = IMWLVLQ + DMEW_LOV;
THWLVLQ = IHWLVLQ + DHIW_LOV;
TLWMVLQ = ILWMVLQ + DLOW_MEV;
TMWMVLQ = IMWMVLQ + DMEW_MEV;
THWMVLQ = IHWMVLQ + DHIW_MEV;
TLWHVLQ = ILWHVLQ + DLOW_HIV;
TMWHVLQ = IMWHVLQ + DMEW_HIV;
THWHVLQ = IHWHVLQ + DHIW_HIV;
...
PLOT(PLWLVLQ PMWLVLQ PHWLVLQ PLWMVLQ PMWMVLQ PHWMVLQ
PLWHVLQ PMWHVLQ PHWHVLQ
PLWLVMQ PMWLVMQ PHWLVMQ PLWMVMQ PMWMVMQ PHWMVMQ
PLWHVMQ PMWHVMQ PHWHVMQ
PLWLVHQ PMWLVHQ PHWLVHQ PLWMVHQ PMWMVHQ PHWMVHQ
PLWHVHQ PMWHVHQ PHWHVHQ);
LOOP(XVAL,-3,3,0.1);
PLWLVLQ = ILWLVLQ*XVAL;
PMWLVLQ = IMWLVLQ*XVAL;
PHWLVLQ = IHWLVLQ*XVAL;
PLWMVLQ = ILWMVLQ*XVAL;
PMWMVLQ = IMWMVLQ*XVAL;
PHWMVLQ = IHWMVLQ*XVAL;
...

第十三步，我们使用循环来计算不同X值下的条件间接效应值，从而绘制出条件间接效应的曲线。循环变量XVAL从-3到3，步长为0.1。这里相当于把之前计算好的不同调节变量组合下的间接效应乘以XVAL，便于作图。

代码解读14

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;
TLWLVLQ = ILWLVLQ + DLOW_LOV;
TMWLVLQ = IMWLVLQ + DMEW_LOV;
THWLVLQ = IHWLVLQ + DHIW_LOV;
TLWMVLQ = ILWMVLQ + DLOW_MEV;
TMWMVLQ = IMWMVLQ + DMEW_MEV;
THWMVLQ = IHWMVLQ + DHIW_MEV;
TLWHVLQ = ILWHVLQ + DLOW_HIV;
TMWHVLQ = IMWHVLQ + DMEW_HIV;
THWHVLQ = IHWHVLQ + DHIW_HIV;
...
PLOT(PLWLVLQ PMWLVLQ PHWLVLQ PLWMVLQ PMWMVLQ PHWMVLQ
PLWHVLQ PMWHVLQ PHWHVLQ
PLWLVMQ PMWLVMQ PHWLVMQ PLWMVMQ PMWMVMQ PHWMVMQ
PLWHVMQ PMWHVMQ PHWHVMQ
PLWLVHQ PMWLVHQ PHWLVHQ PLWMVHQ PMWMVHQ PHWMVHQ
PLWHVHQ PMWHVHQ PHWHVHQ);
LOOP(XVAL,-3,3,0.1);
PLWLVLQ = ILWLVLQ*XVAL;
PMWLVLQ = IMWLVLQ*XVAL;
PHWLVLQ = IHWLVLQ*XVAL;
PLWMVLQ = ILWMVLQ*XVAL;
PMWMVLQ = IMWMVLQ*XVAL;
PHWMVLQ = IHWMVLQ*XVAL;
...
PLOT:
 TYPE = plot2;

第十四步，我们设置图的类型为散点图。

代码解读15

USEVARIABLES = X1 X2 X3 X4 M1 M2 M3 M4
W1 W2 W3 W4 V1 V2 V3 V4 Q1 Q2 Q3 Q4
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;
 Q BY Q1* Q2 Q3 Q4;
 Y BY Y1 Y2 Y3 Y4;
 W@1;  V@1;  Q@1;
MV | M XWITH V;
 MQ | M XWITH Q;
 XW | X XWITH W;
 XV | X XWITH V;
 VQ | V XWITH Q;
 MVQ | M XWITH VQ;
Y ON M (b1);
 Y ON Q (b2);
 Y ON MV (b3);
 Y ON MQ (b4);
 Y ON VQ (b5);
 Y ON MVQ (b6);
 Y ON X (cdash1);
 Y ON W (cdash2);
 Y ON XW (cdash3);
 Y ON V (cdash4);
 Y ON XV (cdash5);
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_Q MED_Q HIGH_Q
 ILWLVLQ IMWLVLQ IHWLVLQ ILWMVLQ IMWMVLQ IHWMVLQ
 ILWHVLQ IMWHVLQ IHWHVLQ
 ILWLVMQ IMWLVMQ IHWLVMQ ILWMVMQ IMWMVMQ IHWMVMQ
 ILWHVMQ IMWHVMQ IHWHVMQ
 ILWLVHQ IMWLVHQ IHWLVHQ ILWMVHQ IMWMVHQ IHWMVHQ
 ILWHVHQ IMWHVHQ IHWHVHQ
 DLOW_LOV DMEW_LOV DHIW_LOV DLOW_MEV DMEW_MEV DHIW_MEV
 DLOW_HIV DMEW_HIV DHIW_HIV
 TLWLVLQ TMWLVLQ THWLVLQ TLWMVLQ TMWMVLQ THWMVLQ
 TLWHVLQ TMWHVLQ THWHVLQ
 TLWLVMQ TMWLVMQ THWLVMQ TLWMVMQ TMWMVMQ THWMVMQ
 TLWHVMQ TMWHVMQ THWHVMQ
 TLWLVHQ TMWLVHQ THWLVHQ TLWMVHQ TMWMVHQ THWMVHQ
 TLWHVHQ TMWHVHQ THWHVHQ);
LOW_W = -1;
 MED_W = 0;
 HIGH_W = 1;
 LOW_V = -1;
 MED_V = 0;
 HIGH_V = 1;
 LOW_Q = -1;
 MED_Q = 0;
 HIGH_Q = 1;
ILWLVLQ = a1*b1 + a3*b1*LOW_W + a1*b3*LOW_V + a3*b3*LOW_W*LOW_V +
a1*b4*LOW_Q + a3*b4*LOW_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*LOW_W*LOW_V*LOW_Q;
IMWLVLQ = a1*b1 + a3*b1*MED_W + a1*b3*LOW_V + a3*b3*MED_W*LOW_V +
a1*b4*LOW_Q + a3*b4*MED_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*MED_W*LOW_V*LOW_Q;
IHWLVLQ = a1*b1 + a3*b1*HIGH_W + a1*b3*LOW_V + a3*b3*HIGH_W*LOW_V +
a1*b4*LOW_Q + a3*b4*HIGH_W*LOW_Q + a1*b6*LOW_V*LOW_Q +
a3*b6*HIGH_W*LOW_V*LOW_Q;
...
DLOW_LOV = cdash1 + cdash3*LOW_W + cdash5*LOW_V;
DMEW_LOV = cdash1 + cdash3*MED_W + cdash5*LOW_V;
DHIW_LOV = cdash1 + cdash3*HIGH_W + cdash5*LOW_V;
DLOW_MEV = cdash1 + cdash3*LOW_W + cdash5*MED_V;
DMEW_MEV = cdash1 + cdash3*MED_W + cdash5*MED_V;
DHIW_MEV = cdash1 + cdash3*HIGH_W + cdash5*MED_V;
DLOW_HIV = cdash1 + cdash3*LOW_W + cdash5*HIGH_V;
DMEW_HIV = cdash1 + cdash3*MED_W + cdash5*HIGH_V;
DHIW_HIV = cdash1 + cdash3*HIGH_W + cdash5*HIGH_V;
TLWLVLQ = ILWLVLQ + DLOW_LOV;
TMWLVLQ = IMWLVLQ + DMEW_LOV;
THWLVLQ = IHWLVLQ + DHIW_LOV;
TLWMVLQ = ILWMVLQ + DLOW_MEV;
TMWMVLQ = IMWMVLQ + DMEW_MEV;
THWMVLQ = IHWMVLQ + DHIW_MEV;
TLWHVLQ = ILWHVLQ + DLOW_HIV;
TMWHVLQ = IMWHVLQ + DMEW_HIV;
THWHVLQ = IHWHVLQ + DHIW_HIV;
...
PLOT(PLWLVLQ PMWLVLQ PHWLVLQ PLWMVLQ PMWMVLQ PHWMVLQ
PLWHVLQ PMWHVLQ PHWHVLQ
PLWLVMQ PMWLVMQ PHWLVMQ PLWMVMQ PMWMVMQ PHWMVMQ
PLWHVMQ PMWHVMQ PHWHVMQ
PLWLVHQ PMWLVHQ PHWLVHQ PLWMVHQ PMWMVHQ PHWMVHQ
PLWHVHQ PMWHVHQ PHWHVHQ);
LOOP(XVAL,-3,3,0.1);
PLWLVLQ = ILWLVLQ*XVAL;
PMWLVLQ = IMWLVLQ*XVAL;
PHWLVLQ = IHWLVLQ*XVAL;
PLWMVLQ = ILWMVLQ*XVAL;
PMWMVLQ = IMWMVLQ*XVAL;
PHWMVLQ = IHWMVLQ*XVAL;
...
PLOT:
 TYPE = plot2;
OUTPUT:
 CINT;

最后，我们请求输出置信区间，以便更全面地分析模型结果。

资源汇总

• 本视频讲义地址: https://mlln.cn/mplus-model-templates/model44latent.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

感谢大家的收看！ 本节课的资源已全部提供，请大家点击页面上的链接下载或查看。 希望这份资料对大家的学习有所帮助，也欢迎大家点赞收藏，方便日后查阅！