I only have 1 IV and 1 DV, plus 1 moderator. I used multiple regression and I am not entirely sure how to present it well. If anyone can provide any guides, I would very much appreciate it. Thank you!
@David L Morgan, yes it is significant. However, I am really not quite sure whether to use Moderation Regression or Hierarchical Logistic Regression. Thank you very much for taking the time to respond!
Hierarchical Logistic Regression would only apply if you have a binary (1 or 0) dependent variable. So, if your independent and dependent variables are both continuous, and your moderator variable is binary, then that is a classic example of moderation.
Here is an online introduction to interaction effects in regression.
It depends on which approach did you use. but here are some common steps you can follow:
Begin by stating your research question and hypotheses. For example, you might be interested in examining the relationship between the IV and DV, and whether this relationship is moderated by the moderator variable.
Describe your sample, including relevant demographic information and any sampling procedures used.
Report the descriptive statistics for your IV, DV, and moderator variable, including the mean, standard deviation, and range of scores.
Conduct preliminary analyses to check for outliers, normality, and multicollinearity. You can report these analyses in a separate section or include them as a footnote to your results.
Conduct the multiple regression analysis, including the IV, moderator variable, and their interaction term. Make sure to check for the assumptions of linearity, homoscedasticity, and independence.
Report the results of the multiple regression analysis in a table. Include the beta coefficients, standard errors, t-values, and p-values for each predictor variable, as well as the R-squared value and any other relevant statistics (such as the F-statistic and degrees of freedom).
Interpret the results of the multiple regression analysis. Describe the main effects of the IV and moderator variable, as well as the interaction between them. You can also include a graph to help illustrate the interaction effect. For example, in R it is called interaction plot.
Finally, discuss the implications of your findings and their limitations. Identify any future research directions and potential practical applications of your results.
Remember to use clear and concise language, and to include enough detail so that readers can understand your methods and results.
David L Morgan thank you so much, I appreciate your kind responses. This link would help me understand more about the interaction effects in regression.
Wadie Abu Dahoud the steps are indeed very helpful as it would surely guide me to explain consicely the results of my data. Other studies have different ways of presenting their data, and this was where I am most confused as I don't know much of the flow when presenting and analyzing data with a moderating variable. Thank you very much for this!
There are questions you should ask yourself before creating the design matrix: Do you want a moderated regression model for all groups or a subgroup in the analysis? Do you have experimental conditions or natural groups as an iv (like sex or race)? Because you didn’t indicate this information, I am giving you a source to cover all bases for building the design matrix, standardizing the iv or moderator, creating the interaction term, building in effects code/dummy codes if your iv is dichotomous, and interpreting the results; the results can be found here: Article Experimental Personality Designs: Analyzing Categorical by C...