For non-linear two-way interactions (including generalised linear models), you might want to use one of the following templates:
對於非線性雙向交互作用 (包括廣義線性模型)，您可能需要使用下列範本之一：

• Quadratic_two-way_interactions.xls - for plotting curvilinear interactions between a quadratic main effect and a moderator (see below)
  Quadratic_two-way_interactions.xls - 用於繪圖二次主效應與調節因子之間的曲線交互作用（請參閱下文）。
• 2-way_logistic_interactions.xls - for plotting interactions from binary logistic regression
  2-way_logistic_interactions.xls - 用於繪圖二元邏輯迴歸的交互作用
• 2-way_poisson_interactions.xls - for plotting interactions from generalised linear models with a Poisson outcome. Also works for any other outcome using a log link (including negative binomial regression)
  2-way_poisson_interactions.xls - 用來繪製泊松結果的廣義線性模型的交互作用。也適用於使用對數連結的任何其他結果 (包括負二叉回歸)

A note about centred and standardised variables. Centred variables are the same as the original version, with the variable mean subtracted so that the new mean is zero.
關於居中變數和標準化變數的說明。居中變數與原始版本相同，只是減去變數的平均值，使新的平均值為零。
Standardised variables are those that are both centred around zero and are scaled so that they have a standard deviation of 1. Following Aiken and West (1991), I recommend that for analysis variables are centred.
標準化變數是指 都是以零為中心，且比例為 跟隨 Aiken 和 West (1991)，我建議在分析時 變數居中。
Some researchers may prefer to use standardised variables. Each gives some advantages in interpreting the coefficients - see Dawson (2014) for more about this (reference below).
有些研究人員可能偏好使用標準化變數。每種變量都提供了一些 解釋係數的優勢 - 請參閱 Dawson (2014) 以獲得更多相關資訊（參考資料如下）。
However, the results obtained should be identical whichever method you use.
然而 所得結果應完全相同。 您使用的方法。
If you choose to analyse centred (or standardised) variables, you should use the regular versions of the Excel templates, and enter the mean of the variables as zero (and standard deviation as 1 if using standardised versions).
如果您選擇以分析為中心 (或標準化）變數，您應該使用 Excel 範本的一般版本、 並輸入變數的平均值為零（如果使用標準化版本，則標準差為 1）。
And for those readers who use the US version of English, for "centred" and "standardised", read "centered" and "standardized"!
對於使用美國版英語的讀者，"centred 「和 」standardised 「應為 」centered 「和 」standardized"！

Three-way interactions 三方互動

To test for three-way interactions (often thought of as a relationship between a variable X and dependent variable Y, moderated by variables Z and W), run a regression analysis, including all three independent variables, all three pairs of two-way interaction terms, and the three-way interaction term.
為了測試三方互動（通常 之間的關係 變數 X 與因變數 Y，由 變數 Z 和 W），執行回歸分析、 包括 所有三個自變量、所有三對 雙向互動項、 和三方互動項。
It is recommended that all the independent variable are centred (or standardised) before calculation of the product terms, although this is not essential. As with two-way interactions, the interaction terms themselves should not be centred (or standardised) after calculation.
建議在計算乘積項目之前，先將所有自變數居中（或標準化）、 雖然這並非必要條件。如 與雙向互動，互動項 自己不應 計算後居中（或標準化）。
The three-way interaction term should be significant in the regression equation in order for the interaction to be interpretable.
三方 互動項應為 在迴歸方程式中顯著，以便 的互動 可解釋。

If you wish to use the Dawson & Richter (2006) test for differences between slopes, you should request the coefficient covariance matrix as part of the regression output.
如果您希望使用 Dawson & Richter (2006) 測試差異 斜率之間，您應該要求系數 作為 回歸輸出。
If you are using SPSS, this can be done by selecting "Covariance matrix" in the "Regression Coefficients" section of the "Statistics" dialog box.
如果您使用 SPSS，此 可透過選擇 「回归系数 」中的 「协方差矩阵」 區段 的「統計」對話方塊。
Note that the variance of a coefficient is the covariance of that coefficient with itself - i.e. can be found on the diagonal of the coefficient covariance matrix.
請注意 係數的方差就是該係數的協方差。 與其本身的系數 - 即可以在 係數共變數矩陣的對角線。

You can then plot the interaction effect using the following Excel template. You will need to enter the unstandardised regression coefficients (including intercept/constant) and means & standard deviations of the three independent variables (X, Z and W) in the cells indicated.
然後，您可以使用下列 Excel 模版來繪製交互作用效果圖。您需要在指定的單元格中輸入三個自變量 (X、Z 和 W) 的非標準化迴歸係數（包括截距/常數）、平均值和標準差。
If you have control variables in your regression, the values of the dependent variable displayed on the plot will be inaccurate unless you centre (or standardise) all control variables first (although even if you don’t the pattern, and therefore the interpretation, will be correct).
如果您在迴歸中有控制變數，除非您先將所有控制變數居中（或標準化），否則因變數在繪圖上顯示的值會不準確（雖然即使您沒有居中，模式以及詮釋也會正確）。
To use the test of slope differences, you should also enter the covariances of the XZ, XW and XZW coefficients from the coefficient covariance matrix, and the total number of cases and number of control variables in your regression.
要使用斜率差測試，您還應該輸入系數共變異矩陣中 XZ、XW 和 XZW 系數的共變異，以及迴歸中的個案總數和控制變數數。
If any of your variables is binary, ensure you enter the actual values of this variable where stated. 3-way_linear_interactions.xls
如果您的任何變數是二進位變數，請確保在註明處輸入該變數的實際值。3-way_linear_interactions.xls

Simple slope tests. As with the 2-way interactions above, this template also allows you to perform simple slope tests, as well as the slope difference tests. See my warnings above about the use of simple slope tests, however.
簡單斜率測試。與上面的 2 向交互作用一樣，此模板也允許您執行簡單斜率測試以及斜率差異測試。但是，請參閱我在上面關於使用簡單斜率測試的警告。