It may give you a bit of a headache to have 8 dummy coefficients for each of your three brand commitment items though. Penalized regression (see " Continuous dependent variable with ordinal independent variable") works well for ordinal predictors.If you think the three brand commitment items measure different constructs, or want to estimate their relationships separately for some other reason (and are prepared to tangle with potential multicollinearity problems).This assumes measurement error balances out, but it may not. and you want to go the quick and dirty route, you can adopt the usual classical test theory assumptions, take the average or sum of the three items' Likert ratings, and enter this as a single continuous predictor. This will allow control of measurement error. and you have a lot of data and motivation to do things right, you can estimate a latent continuous construct with a rating scale model à la item response theory, then add the latent factor as a single continuous predictor. If you think the three brand commitment items measure the same latent construct.
There are a few options to consider here: It is important to have both the main effects in the model when including their interaction, and you may want to center the variables before multiplying them to handle nonessential multicollinearity (I've read in places that this is not much of a solution though, and haven't got a better one offhand).īrand commitment is ordinal though, so ANOVA is not appropriate (I wonder if review valence might be ordinal too) – it wastes information by ignoring the order of ranks. To test for interaction / moderation (basically synonymous), first add brand commitment as a predictor in your linear model, then multiply brand commitment by review valence, and add the product to the model too. Also, should I compute a new variable that combines the 3 statements in one new variable for the analysis.Īny insights that you can provide me with, will be highly appreciated. My question is how can I add this brand commitment "interaction or moderation" in the ANOVA or should I use a different method to analyse it.
I predicted that brand commitment will moderate the effect of the review on the DV. I want to understand what is the interaction between brand commitment and review valence, and how it affects the DV. Brand commitment is high/low if the scores are in the upper/lower third of the scale. Brand commitment is measured by giving a score on a scale from 1-9(fully disagree/fully agree) for 3 statements (taken from previous paper). I also gathered data for the brand commitment of each participant in the experiment. I want to see how these factors affect purchase probability. The factors for the ANOVA are review valence (3 levels) and presence of brand (2 levels). I am running an univariate ANOVA in SPSS to test my hypotheses for my 3x2 between subjects design experiment.