Mplus model73 模型讲解

来自图书《MPlus中介调节模型》

调节中介模型分析教程结构

• 理论模型：详细阐述模型中变量间的概念关系，以及中介、调节效应的理论基础。
• 数学模型：将理论模型转化为具体的数学方程式，明确各变量之间的数学关系，包括主效应、交互效应。
• 数学推导：推导计算间接效应和条件效应的代数公式，为后续模型检验提供理论依据。
• 代码解读：详细解读 Mplus 代码，包括如何构建交互项、使用约束检验条件间接效应，以及绘制条件间接效应图。

大家好，今天我们来介绍一个关于调节中介模型分析的教程。这个教程结构严谨，旨在帮助大家深入理解并应用复杂的调节中介模型。首先，我们会从理论层面出发，详细讲解模型中变量之间的概念关系，以及中介效应和调节效应的理论基础。接着，我们将把理论模型转化为具体的数学方程式，明确各变量之间主效应和交互效应的数学关系。然后，我们会进行数学推导，推导出计算间接效应和条件效应的代数公式，为后续的模型检验提供理论依据。最后，我们会详细解读Mplus代码，包括如何构建交互项，如何使用约束检验条件间接效应，以及如何绘制条件间接效应图。通过这个教程，大家可以全面掌握调节中介模型的分析方法，并将其应用于实际研究中。

理论模型

我们来看，这个模型中有五个变量，分别是X、M、W、Z和Y。箭头表示变量之间的影响关系。例如，X直接影响M和Y，W也直接影响M和Y，Z也直接影响M和Y，M又会影响Y。此外，W和Z还会互相作用影响M和Y。X，W和Z也会相互影响M和Y。

数学模型

这张图展示了一个复杂的统计模型。其中，X、W和Z这三个变量会影响中间变量M。X、W、Z，以及它们的组合XW、XZ和WZ，还有更复杂的组合XWZ，都指向M。M又会影响结果变量Y。此外，X、W、Z、XW、XZ、WZ、XWZ，还有M与W的组合MW、M与Z的组合MZ，以及M、W、Z三者的组合MWZ，也都直接指向Y。图中箭头上的a1到a7，表示X、W、Z和它们的组合对M的影响大小。b1到b4，表示M和它的组合对Y的影响大小。c1’到c7’，表示X、W、Z和它们的组合对Y的直接影响。

数学公式1

Y = b0 + b1M + b2MW + b3MZ + b4MWZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
M = a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ

首先，我们有两个方程。第一个方程描述了因变量 Y 与中介变量 M 以及调节变量 W 和 Z 的关系。第二个方程描述了中介变量 M 与自变量 X 以及调节变量 W 和 Z 的关系。我们的目标是将 M 的表达式代入 Y 的表达式，以便将 Y 表示为 X 的函数。

数学公式2

Y = b0 + b1M + b2MW + b3MZ + b4MWZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
M = a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ
Y = b0 + b1(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ) + b2(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)W + b3(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)Z + b4(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)WZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ

接下来，我们将 M 的表达式代入 Y 的表达式中。这里可以看到，我们将M替换为了包含X,W,Z的复杂表达式。

数学公式3

Y = b0 + b1M + b2MW + b3MZ + b4MWZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
M = a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ
Y = b0 + b1(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ) + b2(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)W + b3(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)Z + b4(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)WZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1Z + a4b1XW + a5b1XZ + a6b1WZ + a7b1XWZ + a0b2W + a1b2XW + a2b2WW + a3b2ZW + a4b2XWW + a5b2XZW + a6b2WWZ + a7b2XWWZ + a0b3Z + a1b3XZ + a2b3WZ + a3b3ZZ + a4b3XWZ + a5b3XZZ + a6b3WZZ + a7b3XWZZ + a0b4WZ + a1b4XWZ + a2b4WWZ + a3b4WZZ + a4b4XWWZ + a5b4XWZZ + a6b4WWZZ + a7b4XWWZZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ

现在，我们展开所有的括号，进行乘法运算。这个步骤看起来很复杂，但实际上只是简单的代数展开。

数学公式4

Y = b0 + b1M + b2MW + b3MZ + b4MWZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
M = a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ
Y = b0 + b1(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ) + b2(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)W + b3(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)Z + b4(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)WZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1Z + a4b1XW + a5b1XZ + a6b1WZ + a7b1XWZ + a0b2W + a1b2XW + a2b2WW + a3b2ZW + a4b2XWW + a5b2XZW + a6b2WWZ + a7b2XWWZ + a0b3Z + a1b3XZ + a2b3WZ + a3b3ZZ + a4b3XWZ + a5b3XZZ + a6b3WZZ + a7b3XWZZ + a0b4WZ + a1b4XWZ + a2b4WWZ + a3b4WZZ + a4b4XWWZ + a5b4XWZZ + a6b4WWZZ + a7b4XWWZZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = (b0 + a0b1 + a2b1W + a3b1Z + a6b1WZ + a0b2W + a2b2WW + a3b2ZW + a6b2WWZ + a0b3Z + a2b3WZ + a3b3ZZ + a6b3WZZ + a0b4WZ + a2b4WWZ + a3b4WZZ + a6b4WWZZ+ c2W + c3'Z + c6'WZ) + (a1b1 + a4b1W + a5b1Z + a7b1WZ + a1b2W + a4b2WW + a5b2ZW + a7b2WWZ + a1b3Z + a4b3WZ + a5b3ZZ + a7b3WZZ + a1b4WZ + a4b4WWZ + a5b4WZZ + a7b4WWZZ + c1' + c4'W + c5'Z + c7'WZ)X

接下来，我们将上式按照 Y = a + bX 的形式进行整理。我们把所有不包含 X 的项放在一起，然后提取出包含 X 的项，得到一个关于 X 的系数。

数学公式5

Y = b0 + b1M + b2MW + b3MZ + b4MWZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
M = a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ
Y = b0 + b1(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ) + b2(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)W + b3(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)Z + b4(a0 + a1X + a2W + a3Z + a4XW + a5XZ + a6WZ + a7XWZ)WZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = b0 + a0b1 + a1b1X + a2b1W + a3b1Z + a4b1XW + a5b1XZ + a6b1WZ + a7b1XWZ + a0b2W + a1b2XW + a2b2WW + a3b2ZW + a4b2XWW + a5b2XZW + a6b2WWZ + a7b2XWWZ + a0b3Z + a1b3XZ + a2b3WZ + a3b3ZZ + a4b3XWZ + a5b3XZZ + a6b3WZZ + a7b3XWZZ + a0b4WZ + a1b4XWZ + a2b4WWZ + a3b4WZZ + a4b4XWWZ + a5b4XWZZ + a6b4WWZZ + a7b4XWWZZ + c1'X + c2W + c3'Z + c4'XW + c5'XZ + c6'WZ + c7'XWZ
Y = (b0 + a0b1 + a2b1W + a3b1Z + a6b1WZ + a0b2W + a2b2WW + a3b2ZW + a6b2WWZ + a0b3Z + a2b3WZ + a3b3ZZ + a6b3WZZ + a0b4WZ + a2b4WWZ + a3b4WZZ + a6b4WWZZ+ c2W + c3'Z + c6'WZ) + (a1b1 + a4b1W + a5b1Z + a7b1WZ + a1b2W + a4b2WW + a5b2ZW + a7b2WWZ + a1b3Z + a4b3WZ + a5b3ZZ + a7b3WZZ + a1b4WZ + a4b4WWZ + a5b4WZZ + a7b4WWZZ + c1' + c4'W + c5'Z + c7'WZ)X
Indirect effect = a1b1 + a4b1W + a5b1Z + a7b1WZ + a1b2W + a4b2WW + a5b2ZW + a7b2WWZ + a1b3Z + a4b3WZ + a5b3ZZ + a7b3WZZ + a1b4WZ + a4b4WWZ + a5b4WZZ + a7b4WWZZ = (a1 + a4W + a5Z + a7WZ)(b1 + b2W + b3Z + b4WZ)
Direct effect = c1' + c4'W + c5'Z + c7'WZ

最后，我们提取出 X 对 Y 的间接效应和直接效应。间接效应是 X 通过中介变量 M 对 Y 的影响，它取决于调节变量 W 和 Z 的条件。直接效应是 X 对 Y 的直接影响，同样取决于调节变量 W 和 Z 的条件。间接效应可以进一步简化为两个多项式相乘的形式。

代码解读1

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;

第一步，我们定义模型中使用的变量。USEVARIABLES 声明了所有变量，包括自变量X，中介变量M，调节变量W和Z，以及因变量Y。同时还包括了变量之间的交互项，比如XW，XZ等等。接下来，在DEFINE部分，我们创建这些交互项，通过将相应的变量相乘得到。注意，这些交互项必须在USEVARIABLES命令之后定义。

代码解读2

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);

第二步，我们设置分析参数。ANALYSIS部分定义了分析类型为一般模型，使用最大似然估计方法，并设置10000次自助抽样。在MODEL部分，我们定义模型的具体路径。例如，[Y] (b0) 定义了Y的截距为b0，Y ON M (b1)定义了M对Y的回归系数为b1，以此类推，我们为所有路径和截距都指定了名称。

代码解读3

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);
! Use model constraint subcommand to test conditional indirect effects


! You need to pick low, medium and high moderator values for W, Z


! for example, of 1 SD below mean, mean, 1 SD above mean
! 2 moderators, 3 values for each, gives 9 combinations


! arbitrary naming convention for conditional indirect and total effects used below:


! MEV_LOQ = medium value of V and low value of Q, etc.
MODEL CONSTRAINT:
 NEW(LOW_W MED_W HIGH_W LOW_Z MED_Z HIGH_Z
 ILOW_LOZ IMEW_LOZ IHIW_LOZ ILOW_MEZ IMEW_MEZ IHIW_MEZ
 ILOW_HIZ IMEW_HIZ IHIW_HIZ
 DLOW_LOZ DMEW_LOZ DHIW_LOZ DLOW_MEZ DMEW_MEZ DHIW_MEZ
 DLOW_HIZ DMEW_HIZ DHIW_HIZ
 TLOW_LOZ TMEW_LOZ THIW_LOZ TLOW_MEZ TMEW_MEZ THIW_MEZ
 TLOW_HIZ TMEW_HIZ THIW_HIZ);
 LOW_W = #LOWW;
! replace #LOWW in the code with your chosen low value of W

 MED_W = #MEDW;
! replace #MEDW in the code with your chosen medium value of W

 HIGH_W = #HIGHW;
! replace #HIGHW in the code with your chosen high value of W
 LOW_Z = #LOWZ;
! replace #LOWZ in the code with your chosen low value of Z

 MED_Z = #MEDZ;
! replace #MEDZ in the code with your chosen medium value of Z

 HIGH_Z = #HIGHZ;
! replace #HIGHZ in the code with your chosen high value of Z

第三步，我们使用模型约束来检验有条件的间接效应。首先，我们需要为调节变量W和Z选择低、中、高三个值，这里建议使用均值上下一个标准差。因为有两个调节变量，每个变量取三个值，所以一共有九种组合。MODEL CONSTRAINT部分定义了新的变量，用来存储调节变量的取值，以及条件间接效应，条件直接效应和条件总效应的结果。注意，代码中用井号加变量名代替了需要用户提供的具体数值，例如， #LOWW, #MEDW等等，使用的时候需要用户替换为实际数值

代码解读4

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);
! Use model constraint subcommand to test conditional indirect effects


! You need to pick low, medium and high moderator values for W, Z


! for example, of 1 SD below mean, mean, 1 SD above mean
! 2 moderators, 3 values for each, gives 9 combinations


! arbitrary naming convention for conditional indirect and total effects used below:


! MEV_LOQ = medium value of V and low value of Q, etc.
MODEL CONSTRAINT:
 NEW(LOW_W MED_W HIGH_W LOW_Z MED_Z HIGH_Z
 ILOW_LOZ IMEW_LOZ IHIW_LOZ ILOW_MEZ IMEW_MEZ IHIW_MEZ
 ILOW_HIZ IMEW_HIZ IHIW_HIZ
 DLOW_LOZ DMEW_LOZ DHIW_LOZ DLOW_MEZ DMEW_MEZ DHIW_MEZ
 DLOW_HIZ DMEW_HIZ DHIW_HIZ
 TLOW_LOZ TMEW_LOZ THIW_LOZ TLOW_MEZ TMEW_MEZ THIW_MEZ
 TLOW_HIZ TMEW_HIZ THIW_HIZ);
 LOW_W = #LOWW;
! replace #LOWW in the code with your chosen low value of W

 MED_W = #MEDW;
! replace #MEDW in the code with your chosen medium value of W

 HIGH_W = #HIGHW;
! replace #HIGHW in the code with your chosen high value of W
 LOW_Z = #LOWZ;
! replace #LOWZ in the code with your chosen low value of Z

 MED_Z = #MEDZ;
! replace #MEDZ in the code with your chosen medium value of Z

 HIGH_Z = #HIGHZ;
! replace #HIGHZ in the code with your chosen high value of Z
! Calc conditional indirect effects for each combination of moderator values
 ILOW_LOZ = a1*b1 + a4*b1*LOW_W + a5*b1*LOW_Z + a7*b1*LOW_W*LOW_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*LOW_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*LOW_Z + a1*b3*LOW_Z + a4*b3*LOW_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*LOW_W*LOW_Z*LOW_Z + a1*b4*LOW_W*LOW_Z +
 a4*b4*LOW_W*LOW_W*LOW_Z + a5*b4*LOW_W*LOW_Z*LOW_Z +
 a7*b4*LOW_W*LOW_W*LOW_Z*LOW_Z;
 IMEW_LOZ = a1*b1 + a4*b1*MED_W + a5*b1*LOW_Z + a7*b1*MED_W*LOW_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*LOW_Z*MED_W +
 a7*b2*MED_W*MED_W*LOW_Z + a1*b3*LOW_Z + a4*b3*MED_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*MED_W*LOW_Z*LOW_Z + a1*b4*MED_W*LOW_Z +
 a4*b4*MED_W*MED_W*LOW_Z + a5*b4*MED_W*LOW_Z*LOW_Z +
 a7*b4*MED_W*MED_W*LOW_Z*LOW_Z;
 IHIW_LOZ = a1*b1 + a4*b1*HIGH_W + a5*b1*LOW_Z + a7*b1*HIGH_W*LOW_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*LOW_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*LOW_Z + a1*b3*LOW_Z + a4*b3*HIGH_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*HIGH_W*LOW_Z*LOW_Z + a1*b4*HIGH_W*LOW_Z +
 a4*b4*HIGH_W*HIGH_W*LOW_Z + a5*b4*HIGH_W*LOW_Z*LOW_Z +
 a7*b4*HIGH_W*HIGH_W*LOW_Z*LOW_Z;
 ILOW_MEZ = a1*b1 + a4*b1*LOW_W + a5*b1*MED_Z + a7*b1*LOW_W*MED_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*MED_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*MED_Z + a1*b3*MED_Z + a4*b3*LOW_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*LOW_W*MED_Z*MED_Z + a1*b4*LOW_W*MED_Z +
 a4*b4*LOW_W*LOW_W*MED_Z + a5*b4*LOW_W*MED_Z*MED_Z +
 a7*b4*LOW_W*LOW_W*MED_Z*MED_Z;

第四步，我们计算不同调节变量取值组合下的条件间接效应。例如，ILOW_LOZ表示当W和Z都取低值时的间接效应，它的计算公式是基于模型中定义的回归系数和调节变量的取值。其他变量，例如IMEW_LOZ,IHIW_LOZ等都是类似的计算，只不过是W和Z的取值不同，对应于不同组合的调节变量值。

代码解读5

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);
! Use model constraint subcommand to test conditional indirect effects


! You need to pick low, medium and high moderator values for W, Z


! for example, of 1 SD below mean, mean, 1 SD above mean
! 2 moderators, 3 values for each, gives 9 combinations


! arbitrary naming convention for conditional indirect and total effects used below:


! MEV_LOQ = medium value of V and low value of Q, etc.
MODEL CONSTRAINT:
 NEW(LOW_W MED_W HIGH_W LOW_Z MED_Z HIGH_Z
 ILOW_LOZ IMEW_LOZ IHIW_LOZ ILOW_MEZ IMEW_MEZ IHIW_MEZ
 ILOW_HIZ IMEW_HIZ IHIW_HIZ
 DLOW_LOZ DMEW_LOZ DHIW_LOZ DLOW_MEZ DMEW_MEZ DHIW_MEZ
 DLOW_HIZ DMEW_HIZ DHIW_HIZ
 TLOW_LOZ TMEW_LOZ THIW_LOZ TLOW_MEZ TMEW_MEZ THIW_MEZ
 TLOW_HIZ TMEW_HIZ THIW_HIZ);
 LOW_W = #LOWW;
! replace #LOWW in the code with your chosen low value of W

 MED_W = #MEDW;
! replace #MEDW in the code with your chosen medium value of W

 HIGH_W = #HIGHW;
! replace #HIGHW in the code with your chosen high value of W
 LOW_Z = #LOWZ;
! replace #LOWZ in the code with your chosen low value of Z

 MED_Z = #MEDZ;
! replace #MEDZ in the code with your chosen medium value of Z

 HIGH_Z = #HIGHZ;
! replace #HIGHZ in the code with your chosen high value of Z
! Calc conditional indirect effects for each combination of moderator values
 ILOW_LOZ = a1*b1 + a4*b1*LOW_W + a5*b1*LOW_Z + a7*b1*LOW_W*LOW_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*LOW_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*LOW_Z + a1*b3*LOW_Z + a4*b3*LOW_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*LOW_W*LOW_Z*LOW_Z + a1*b4*LOW_W*LOW_Z +
 a4*b4*LOW_W*LOW_W*LOW_Z + a5*b4*LOW_W*LOW_Z*LOW_Z +
 a7*b4*LOW_W*LOW_W*LOW_Z*LOW_Z;
 IMEW_LOZ = a1*b1 + a4*b1*MED_W + a5*b1*LOW_Z + a7*b1*MED_W*LOW_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*LOW_Z*MED_W +
 a7*b2*MED_W*MED_W*LOW_Z + a1*b3*LOW_Z + a4*b3*MED_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*MED_W*LOW_Z*LOW_Z + a1*b4*MED_W*LOW_Z +
 a4*b4*MED_W*MED_W*LOW_Z + a5*b4*MED_W*LOW_Z*LOW_Z +
 a7*b4*MED_W*MED_W*LOW_Z*LOW_Z;
 IHIW_LOZ = a1*b1 + a4*b1*HIGH_W + a5*b1*LOW_Z + a7*b1*HIGH_W*LOW_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*LOW_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*LOW_Z + a1*b3*LOW_Z + a4*b3*HIGH_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*HIGH_W*LOW_Z*LOW_Z + a1*b4*HIGH_W*LOW_Z +
 a4*b4*HIGH_W*HIGH_W*LOW_Z + a5*b4*HIGH_W*LOW_Z*LOW_Z +
 a7*b4*HIGH_W*HIGH_W*LOW_Z*LOW_Z;
 ILOW_MEZ = a1*b1 + a4*b1*LOW_W + a5*b1*MED_Z + a7*b1*LOW_W*MED_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*MED_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*MED_Z + a1*b3*MED_Z + a4*b3*LOW_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*LOW_W*MED_Z*MED_Z + a1*b4*LOW_W*MED_Z +
 a4*b4*LOW_W*LOW_W*MED_Z + a5*b4*LOW_W*MED_Z*MED_Z +
 a7*b4*LOW_W*LOW_W*MED_Z*MED_Z;

IMEW_MEZ = a1*b1 + a4*b1*MED_W + a5*b1*MED_Z + a7*b1*MED_W*MED_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*MED_Z*MED_W +
 a7*b2*MED_W*MED_W*MED_Z + a1*b3*MED_Z + a4*b3*MED_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*MED_W*MED_Z*MED_Z + a1*b4*MED_W*MED_Z +
 a4*b4*MED_W*MED_W*MED_Z + a5*b4*MED_W*MED_Z*MED_Z +
 a7*b4*MED_W*MED_W*MED_Z*MED_Z;
 IHIW_MEZ = a1*b1 + a4*b1*HIGH_W + a5*b1*MED_Z + a7*b1*HIGH_W*MED_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*MED_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*MED_Z + a1*b3*MED_Z + a4*b3*HIGH_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*HIGH_W*MED_Z*MED_Z + a1*b4*HIGH_W*MED_Z +
 a4*b4*HIGH_W*HIGH_W*MED_Z + a5*b4*HIGH_W*MED_Z*MED_Z +
 a7*b4*HIGH_W*HIGH_W*MED_Z*MED_Z;
 ILOW_HIZ = a1*b1 + a4*b1*LOW_W + a5*b1*HIGH_Z + a7*b1*LOW_W*HIGH_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*HIGH_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*LOW_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*LOW_W*HIGH_Z*HIGH_Z + a1*b4*LOW_W*HIGH_Z +
 a4*b4*LOW_W*LOW_W*HIGH_Z + a5*b4*LOW_W*HIGH_Z*HIGH_Z +
 a7*b4*LOW_W*LOW_W*HIGH_Z*HIGH_Z;
 IMEW_HIZ = a1*b1 + a4*b1*MED_W + a5*b1*HIGH_Z + a7*b1*MED_W*HIGH_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*HIGH_Z*MED_W +
 a7*b2*MED_W*MED_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*MED_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*MED_W*HIGH_Z*HIGH_Z + a1*b4*MED_W*HIGH_Z +
 a4*b4*MED_W*MED_W*HIGH_Z + a5*b4*MED_W*HIGH_Z*HIGH_Z +
 a7*b4*MED_W*MED_W*HIGH_Z*HIGH_Z;
 IHIW_HIZ = a1*b1 + a4*b1*HIGH_W + a5*b1*HIGH_Z + a7*b1*HIGH_W*HIGH_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*HIGH_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*HIGH_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*HIGH_W*HIGH_Z*HIGH_Z + a1*b4*HIGH_W*HIGH_Z +
 a4*b4*HIGH_W*HIGH_W*HIGH_Z + a5*b4*HIGH_W*HIGH_Z*HIGH_Z +
 a7*b4*HIGH_W*HIGH_W*HIGH_Z*HIGH_Z;

第五步，继续计算剩余的条件间接效应组合。和第四步类似，这些代码计算了不同W和Z的组合，包括中等W低Z(IMEW_LOZ),高W低Z(IHIW_LOZ),低W中Z(ILOW_MEZ),中W中Z(IMEW_MEZ),高W中Z(IHIW_MEZ),低W高Z(ILOW_HIZ),中W高Z(IMEW_HIZ),和高W高Z(IHIW_HIZ)下的条件间接效应，公式都是基于之前定义的回归系数和调节变量值。

代码解读6

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);
! Use model constraint subcommand to test conditional indirect effects


! You need to pick low, medium and high moderator values for W, Z


! for example, of 1 SD below mean, mean, 1 SD above mean
! 2 moderators, 3 values for each, gives 9 combinations


! arbitrary naming convention for conditional indirect and total effects used below:


! MEV_LOQ = medium value of V and low value of Q, etc.
MODEL CONSTRAINT:
 NEW(LOW_W MED_W HIGH_W LOW_Z MED_Z HIGH_Z
 ILOW_LOZ IMEW_LOZ IHIW_LOZ ILOW_MEZ IMEW_MEZ IHIW_MEZ
 ILOW_HIZ IMEW_HIZ IHIW_HIZ
 DLOW_LOZ DMEW_LOZ DHIW_LOZ DLOW_MEZ DMEW_MEZ DHIW_MEZ
 DLOW_HIZ DMEW_HIZ DHIW_HIZ
 TLOW_LOZ TMEW_LOZ THIW_LOZ TLOW_MEZ TMEW_MEZ THIW_MEZ
 TLOW_HIZ TMEW_HIZ THIW_HIZ);
 LOW_W = #LOWW;
! replace #LOWW in the code with your chosen low value of W

 MED_W = #MEDW;
! replace #MEDW in the code with your chosen medium value of W

 HIGH_W = #HIGHW;
! replace #HIGHW in the code with your chosen high value of W
 LOW_Z = #LOWZ;
! replace #LOWZ in the code with your chosen low value of Z

 MED_Z = #MEDZ;
! replace #MEDZ in the code with your chosen medium value of Z

 HIGH_Z = #HIGHZ;
! replace #HIGHZ in the code with your chosen high value of Z
! Calc conditional indirect effects for each combination of moderator values
 ILOW_LOZ = a1*b1 + a4*b1*LOW_W + a5*b1*LOW_Z + a7*b1*LOW_W*LOW_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*LOW_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*LOW_Z + a1*b3*LOW_Z + a4*b3*LOW_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*LOW_W*LOW_Z*LOW_Z + a1*b4*LOW_W*LOW_Z +
 a4*b4*LOW_W*LOW_W*LOW_Z + a5*b4*LOW_W*LOW_Z*LOW_Z +
 a7*b4*LOW_W*LOW_W*LOW_Z*LOW_Z;
 IMEW_LOZ = a1*b1 + a4*b1*MED_W + a5*b1*LOW_Z + a7*b1*MED_W*LOW_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*LOW_Z*MED_W +
 a7*b2*MED_W*MED_W*LOW_Z + a1*b3*LOW_Z + a4*b3*MED_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*MED_W*LOW_Z*LOW_Z + a1*b4*MED_W*LOW_Z +
 a4*b4*MED_W*MED_W*LOW_Z + a5*b4*MED_W*LOW_Z*LOW_Z +
 a7*b4*MED_W*MED_W*LOW_Z*LOW_Z;
 IHIW_LOZ = a1*b1 + a4*b1*HIGH_W + a5*b1*LOW_Z + a7*b1*HIGH_W*LOW_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*LOW_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*LOW_Z + a1*b3*LOW_Z + a4*b3*HIGH_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*HIGH_W*LOW_Z*LOW_Z + a1*b4*HIGH_W*LOW_Z +
 a4*b4*HIGH_W*HIGH_W*LOW_Z + a5*b4*HIGH_W*LOW_Z*LOW_Z +
 a7*b4*HIGH_W*HIGH_W*LOW_Z*LOW_Z;
 ILOW_MEZ = a1*b1 + a4*b1*LOW_W + a5*b1*MED_Z + a7*b1*LOW_W*MED_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*MED_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*MED_Z + a1*b3*MED_Z + a4*b3*LOW_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*LOW_W*MED_Z*MED_Z + a1*b4*LOW_W*MED_Z +
 a4*b4*LOW_W*LOW_W*MED_Z + a5*b4*LOW_W*MED_Z*MED_Z +
 a7*b4*LOW_W*LOW_W*MED_Z*MED_Z;

IMEW_MEZ = a1*b1 + a4*b1*MED_W + a5*b1*MED_Z + a7*b1*MED_W*MED_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*MED_Z*MED_W +
 a7*b2*MED_W*MED_W*MED_Z + a1*b3*MED_Z + a4*b3*MED_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*MED_W*MED_Z*MED_Z + a1*b4*MED_W*MED_Z +
 a4*b4*MED_W*MED_W*MED_Z + a5*b4*MED_W*MED_Z*MED_Z +
 a7*b4*MED_W*MED_W*MED_Z*MED_Z;
 IHIW_MEZ = a1*b1 + a4*b1*HIGH_W + a5*b1*MED_Z + a7*b1*HIGH_W*MED_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*MED_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*MED_Z + a1*b3*MED_Z + a4*b3*HIGH_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*HIGH_W*MED_Z*MED_Z + a1*b4*HIGH_W*MED_Z +
 a4*b4*HIGH_W*HIGH_W*MED_Z + a5*b4*HIGH_W*MED_Z*MED_Z +
 a7*b4*HIGH_W*HIGH_W*MED_Z*MED_Z;
 ILOW_HIZ = a1*b1 + a4*b1*LOW_W + a5*b1*HIGH_Z + a7*b1*LOW_W*HIGH_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*HIGH_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*LOW_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*LOW_W*HIGH_Z*HIGH_Z + a1*b4*LOW_W*HIGH_Z +
 a4*b4*LOW_W*LOW_W*HIGH_Z + a5*b4*LOW_W*HIGH_Z*HIGH_Z +
 a7*b4*LOW_W*LOW_W*HIGH_Z*HIGH_Z;
 IMEW_HIZ = a1*b1 + a4*b1*MED_W + a5*b1*HIGH_Z + a7*b1*MED_W*HIGH_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*HIGH_Z*MED_W +
 a7*b2*MED_W*MED_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*MED_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*MED_W*HIGH_Z*HIGH_Z + a1*b4*MED_W*HIGH_Z +
 a4*b4*MED_W*MED_W*HIGH_Z + a5*b4*MED_W*HIGH_Z*HIGH_Z +
 a7*b4*MED_W*MED_W*HIGH_Z*HIGH_Z;
 IHIW_HIZ = a1*b1 + a4*b1*HIGH_W + a5*b1*HIGH_Z + a7*b1*HIGH_W*HIGH_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*HIGH_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*HIGH_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*HIGH_W*HIGH_Z*HIGH_Z + a1*b4*HIGH_W*HIGH_Z +
 a4*b4*HIGH_W*HIGH_W*HIGH_Z + a5*b4*HIGH_W*HIGH_Z*HIGH_Z +
 a7*b4*HIGH_W*HIGH_W*HIGH_Z*HIGH_Z;
! Calc conditional direct effects for each combination of moderator values
 DLOW_LOZ = cdash1 + cdash4*LOW_W + cdash5*LOW_Z + cdash7*LOW_W*LOW_Z;
 DMEW_LOZ = cdash1 + cdash4*MED_W + cdash5*LOW_Z + cdash7*MED_W*LOW_Z;
 DHIW_LOZ = cdash1 + cdash4*HIGH_W + cdash5*LOW_Z + cdash7*HIGH_W*LOW_Z;
 DLOW_MEZ = cdash1 + cdash4*LOW_W + cdash5*MED_Z + cdash7*LOW_W*MED_Z;
 DMEW_MEZ = cdash1 + cdash4*MED_W + cdash5*MED_Z + cdash7*MED_W*MED_Z;
 DHIW_MEZ = cdash1 + cdash4*HIGH_W + cdash5*MED_Z + cdash7*HIGH_W*MED_Z;
 DLOW_HIZ = cdash1 + cdash4*LOW_W + cdash5*HIGH_Z + cdash7*LOW_W*HIGH_Z;
 DMEW_HIZ = cdash1 + cdash4*MED_W + cdash5*HIGH_Z + cdash7*MED_W*HIGH_Z;
 DHIW_HIZ = cdash1 + cdash4*HIGH_W + cdash5*HIGH_Z + cdash7*HIGH_W*HIGH_Z;
! Calc conditional total effects for each combination of moderator values
 TLOW_LOZ = ILOW_LOZ + DLOW_LOZ;
 TMEW_LOZ = IMEW_LOZ + DMEW_LOZ;
 THIW_LOZ = IHIW_LOZ + DHIW_LOZ;
 TLOW_MEZ = ILOW_MEZ + DLOW_MEZ;
 TMEW_MEZ = IMEW_MEZ + DMEW_MEZ;
 THIW_MEZ = IHIW_MEZ + DHIW_MEZ;
 TLOW_HIZ = ILOW_HIZ + DLOW_HIZ;
 TMEW_HIZ = IMEW_HIZ + DMEW_HIZ;
 THIW_HIZ = IHIW_HIZ + DHIW_HIZ;

第六步，计算条件直接效应和条件总效应。首先，我们计算不同调节变量取值组合下的条件直接效应，例如DLOW_LOZ表示W和Z都取低值时的直接效应，它的计算基于模型中的直接效应路径系数。之后，我们计算不同调节变量取值下的条件总效应，它是条件间接效应和条件直接效应的和， 例如 TLOW_LOZ 等于 ILOW_LOZ 和 DLOW_LOZ 的和，以此类推，计算出所有调节变量取值组合下的条件总效应。

代码解读7

USEVARIABLES = X M W Z Y XW XZ WZ MW MZ XWZ MWZ;
! Create interaction terms

! Note that they have to be placed at end of USEVARIABLES subcommand above
DEFINE:

 MW = M*W;
 MZ = M*Z;
 XW = X*W;
 XZ = X*Z;
 WZ = W*Z;
 MWZ = M*W*Z;
 XWZ = X*W*Z;
ANALYSIS:

 TYPE = GENERAL;
 ESTIMATOR = ML;
 BOOTSTRAP = 10000;
! In model statement name each path and intercept using parentheses
MODEL:

 [Y] (b0);
 Y ON M (b1);
 Y ON MW (b2);
 Y ON MZ (b3);
 Y ON MWZ (b4);
 Y ON X(cdash1);
 Y ON W (cdash2);
 Y ON Z (cdash3);
 Y ON XW (cdash4);
 Y ON XZ (cdash5);
 Y ON WZ (cdash6);
 Y ON XWZ (cdash7);
 [M] (a0);
 M ON X (a1);
 M ON W (a2);
 M ON Z (a3);
 M ON XW (a4);
 M ON XZ (a5);
 M ON WZ (a6);
 M ON XWZ (a7);
! Use model constraint subcommand to test conditional indirect effects


! You need to pick low, medium and high moderator values for W, Z


! for example, of 1 SD below mean, mean, 1 SD above mean
! 2 moderators, 3 values for each, gives 9 combinations


! arbitrary naming convention for conditional indirect and total effects used below:


! MEV_LOQ = medium value of V and low value of Q, etc.
MODEL CONSTRAINT:
 NEW(LOW_W MED_W HIGH_W LOW_Z MED_Z HIGH_Z
 ILOW_LOZ IMEW_LOZ IHIW_LOZ ILOW_MEZ IMEW_MEZ IHIW_MEZ
 ILOW_HIZ IMEW_HIZ IHIW_HIZ
 DLOW_LOZ DMEW_LOZ DHIW_LOZ DLOW_MEZ DMEW_MEZ DHIW_MEZ
 DLOW_HIZ DMEW_HIZ DHIW_HIZ
 TLOW_LOZ TMEW_LOZ THIW_LOZ TLOW_MEZ TMEW_MEZ THIW_MEZ
 TLOW_HIZ TMEW_HIZ THIW_HIZ);
 LOW_W = #LOWW;
! replace #LOWW in the code with your chosen low value of W

 MED_W = #MEDW;
! replace #MEDW in the code with your chosen medium value of W

 HIGH_W = #HIGHW;
! replace #HIGHW in the code with your chosen high value of W
 LOW_Z = #LOWZ;
! replace #LOWZ in the code with your chosen low value of Z

 MED_Z = #MEDZ;
! replace #MEDZ in the code with your chosen medium value of Z

 HIGH_Z = #HIGHZ;
! replace #HIGHZ in the code with your chosen high value of Z
! Calc conditional indirect effects for each combination of moderator values
 ILOW_LOZ = a1*b1 + a4*b1*LOW_W + a5*b1*LOW_Z + a7*b1*LOW_W*LOW_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*LOW_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*LOW_Z + a1*b3*LOW_Z + a4*b3*LOW_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*LOW_W*LOW_Z*LOW_Z + a1*b4*LOW_W*LOW_Z +
 a4*b4*LOW_W*LOW_W*LOW_Z + a5*b4*LOW_W*LOW_Z*LOW_Z +
 a7*b4*LOW_W*LOW_W*LOW_Z*LOW_Z;
 IMEW_LOZ = a1*b1 + a4*b1*MED_W + a5*b1*LOW_Z + a7*b1*MED_W*LOW_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*LOW_Z*MED_W +
 a7*b2*MED_W*MED_W*LOW_Z + a1*b3*LOW_Z + a4*b3*MED_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*MED_W*LOW_Z*LOW_Z + a1*b4*MED_W*LOW_Z +
 a4*b4*MED_W*MED_W*LOW_Z + a5*b4*MED_W*LOW_Z*LOW_Z +
 a7*b4*MED_W*MED_W*LOW_Z*LOW_Z;
 IHIW_LOZ = a1*b1 + a4*b1*HIGH_W + a5*b1*LOW_Z + a7*b1*HIGH_W*LOW_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*LOW_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*LOW_Z + a1*b3*LOW_Z + a4*b3*HIGH_W*LOW_Z +
 a5*b3*LOW_Z*LOW_Z + a7*b3*HIGH_W*LOW_Z*LOW_Z + a1*b4*HIGH_W*LOW_Z +
 a4*b4*HIGH_W*HIGH_W*LOW_Z + a5*b4*HIGH_W*LOW_Z*LOW_Z +
 a7*b4*HIGH_W*HIGH_W*LOW_Z*LOW_Z;
 ILOW_MEZ = a1*b1 + a4*b1*LOW_W + a5*b1*MED_Z + a7*b1*LOW_W*MED_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*MED_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*MED_Z + a1*b3*MED_Z + a4*b3*LOW_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*LOW_W*MED_Z*MED_Z + a1*b4*LOW_W*MED_Z +
 a4*b4*LOW_W*LOW_W*MED_Z + a5*b4*LOW_W*MED_Z*MED_Z +
 a7*b4*LOW_W*LOW_W*MED_Z*MED_Z;

IMEW_MEZ = a1*b1 + a4*b1*MED_W + a5*b1*MED_Z + a7*b1*MED_W*MED_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*MED_Z*MED_W +
 a7*b2*MED_W*MED_W*MED_Z + a1*b3*MED_Z + a4*b3*MED_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*MED_W*MED_Z*MED_Z + a1*b4*MED_W*MED_Z +
 a4*b4*MED_W*MED_W*MED_Z + a5*b4*MED_W*MED_Z*MED_Z +
 a7*b4*MED_W*MED_W*MED_Z*MED_Z;
 IHIW_MEZ = a1*b1 + a4*b1*HIGH_W + a5*b1*MED_Z + a7*b1*HIGH_W*MED_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*MED_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*MED_Z + a1*b3*MED_Z + a4*b3*HIGH_W*MED_Z +
 a5*b3*MED_Z*MED_Z + a7*b3*HIGH_W*MED_Z*MED_Z + a1*b4*HIGH_W*MED_Z +
 a4*b4*HIGH_W*HIGH_W*MED_Z + a5*b4*HIGH_W*MED_Z*MED_Z +
 a7*b4*HIGH_W*HIGH_W*MED_Z*MED_Z;
 ILOW_HIZ = a1*b1 + a4*b1*LOW_W + a5*b1*HIGH_Z + a7*b1*LOW_W*HIGH_Z +
 a1*b2*LOW_W + a4*b2*LOW_W*LOW_W + a5*b2*HIGH_Z*LOW_W +
 a7*b2*LOW_W*LOW_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*LOW_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*LOW_W*HIGH_Z*HIGH_Z + a1*b4*LOW_W*HIGH_Z +
 a4*b4*LOW_W*LOW_W*HIGH_Z + a5*b4*LOW_W*HIGH_Z*HIGH_Z +
 a7*b4*LOW_W*LOW_W*HIGH_Z*HIGH_Z;
 IMEW_HIZ = a1*b1 + a4*b1*MED_W + a5*b1*HIGH_Z + a7*b1*MED_W*HIGH_Z +
 a1*b2*MED_W + a4*b2*MED_W*MED_W + a5*b2*HIGH_Z*MED_W +
 a7*b2*MED_W*MED_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*MED_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*MED_W*HIGH_Z*HIGH_Z + a1*b4*MED_W*HIGH_Z +
 a4*b4*MED_W*MED_W*HIGH_Z + a5*b4*MED_W*HIGH_Z*HIGH_Z +
 a7*b4*MED_W*MED_W*HIGH_Z*HIGH_Z;
 IHIW_HIZ = a1*b1 + a4*b1*HIGH_W + a5*b1*HIGH_Z + a7*b1*HIGH_W*HIGH_Z +
 a1*b2*HIGH_W + a4*b2*HIGH_W*HIGH_W + a5*b2*HIGH_Z*HIGH_W +
 a7*b2*HIGH_W*HIGH_W*HIGH_Z + a1*b3*HIGH_Z + a4*b3*HIGH_W*HIGH_Z +
 a5*b3*HIGH_Z*HIGH_Z + a7*b3*HIGH_W*HIGH_Z*HIGH_Z + a1*b4*HIGH_W*HIGH_Z +
 a4*b4*HIGH_W*HIGH_W*HIGH_Z + a5*b4*HIGH_W*HIGH_Z*HIGH_Z +
 a7*b4*HIGH_W*HIGH_W*HIGH_Z*HIGH_Z;
! Calc conditional direct effects for each combination of moderator values
 DLOW_LOZ = cdash1 + cdash4*LOW_W + cdash5*LOW_Z + cdash7*LOW_W*LOW_Z;
 DMEW_LOZ = cdash1 + cdash4*MED_W + cdash5*LOW_Z + cdash7*MED_W*LOW_Z;
 DHIW_LOZ = cdash1 + cdash4*HIGH_W + cdash5*LOW_Z + cdash7*HIGH_W*LOW_Z;
 DLOW_MEZ = cdash1 + cdash4*LOW_W + cdash5*MED_Z + cdash7*LOW_W*MED_Z;
 DMEW_MEZ = cdash1 + cdash4*MED_W + cdash5*MED_Z + cdash7*MED_W*MED_Z;
 DHIW_MEZ = cdash1 + cdash4*HIGH_W + cdash5*MED_Z + cdash7*HIGH_W*MED_Z;
 DLOW_HIZ = cdash1 + cdash4*LOW_W + cdash5*HIGH_Z + cdash7*LOW_W*HIGH_Z;
 DMEW_HIZ = cdash1 + cdash4*MED_W + cdash5*HIGH_Z + cdash7*MED_W*HIGH_Z;
 DHIW_HIZ = cdash1 + cdash4*HIGH_W + cdash5*HIGH_Z + cdash7*HIGH_W*HIGH_Z;
! Calc conditional total effects for each combination of moderator values
 TLOW_LOZ = ILOW_LOZ + DLOW_LOZ;
 TMEW_LOZ = IMEW_LOZ + DMEW_LOZ;
 THIW_LOZ = IHIW_LOZ + DHIW_LOZ;
 TLOW_MEZ = ILOW_MEZ + DLOW_MEZ;
 TMEW_MEZ = IMEW_MEZ + DMEW_MEZ;
 THIW_MEZ = IHIW_MEZ + DHIW_MEZ;
 TLOW_HIZ = ILOW_HIZ + DLOW_HIZ;
 TMEW_HIZ = IMEW_HIZ + DMEW_HIZ;
 THIW_HIZ = IHIW_HIZ + DHIW_HIZ;
! Use loop plot to plot conditional indirect effect of X on Y for each combination of low, med, high moderator values
! Could be edited to show conditional direct or conditional total effects instead
! NOTE - values of 1,5 in LOOP() statement need to be replaced by
! logical min and max limits of predictor X used in analysis
 PLOT(PLOW_LOZ PMEW_LOZ PHIW_LOZ PLOW_MEZ PMEW_MEZ PHIW_MEZ
 PLOW_HIZ PMEW_HIZ PHIW_HIZ);
 LOOP(XVAL,1,5,0.1);
 PLOW_LOZ = ILOW_LOZ*XVAL;
 PMEW_LOZ = IMEW_LOZ*XVAL;
 PHIW_LOZ = IHIW_LOZ*XVAL;
 PLOW_MEZ = ILOW_MEZ*XVAL;
 PMEW_MEZ = IMEW_MEZ*XVAL;
 PHIW_MEZ = IHIW_MEZ*XVAL;
 PLOW_HIZ = ILOW_HIZ*XVAL;
 PMEW_HIZ = IMEW_HIZ*XVAL;
 PHIW_HIZ = IHIW_HIZ*XVAL;
PLOT:

 TYPE = plot2;
OUTPUT:

 STAND CINT(bcbootstrap);

第七步，我们使用循环绘图来展示不同调节变量取值组合下的X对Y的条件间接效应。PLOT部分声明了要绘制的变量。LOOP命令创建一个循环，XVAL从1到5以0.1的步长递增。计算出不同调节变量取值组合下的条件间接效应与XVAL的乘积，用于绘制X与条件间接效应的图。PLOT 部分设置绘图类型为双变量绘图。最后，OUTPUT 部分设置输出标准化系数和偏差校正的自助法置信区间。

资源汇总

• 本视频讲义地址: https://mlln.cn/mplus-model-templates/model73.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

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