Can you help me with spss?

02 February 2016 2 6K Report

Good Morning,

I have a small doubt regarding how to deal with analysis of usage's predictors

I am applying the decomposed theory of planned behaviour to gain a deeper understanding of factors influencing the adoption/usage of mobile recruitment.

I have 3 items for Usership, where Usership1 is related to the actual usage (Have you ever used mobile recruitment apps? Yes0/No1) while Usership2 and Usership3 are scale ranging from 1 to 10 referring to intensity of usage and recency of usage.

The predictor of Usership, is Intention which is represented by 3 items (Intention1,Intention2 and Intention3).

So my questions are:

Should I run a binary logistic regression where my dependent variable is Usership1 and my independent variables are Intention1/2/3? If yes should I consider Intetion items items as categorial covariates? (see the screenshots attached logistic1 and logistic2)

How to analyse Usership2 and Usership3? Should I run 2 separate regression analysis with Intention1/2/3 as independent variables? Or should I use the mean of Intention1/2/3 as independent variable

I hope my explanation is clear

Thanks in advance

Raffaele

Rainer Duesing

Dear Raffaele,

I have some questions:

-regarding your intention variabes in question 1: are they really categorical or just labeled as categorical within SPSS? It is possible to include categorical predictors, but you have to create k-1 (k=amount of categories) variables to code them (e.g. dummy coding, effect coding etc)

- question 2: I don't understand this, if you have two remaining DVs, what would it help to reduce the amount of predictors (as you proposed mean of intuition 1-3)? As a result you would have 2 bivariate regressions: Usership2 with Mean_intention and Usership3 with Mean_intention. Besides that, it makes no sense to calculate a mean for categorical variables (as you suspect them to be caterocial, but see my first question).

Besides my questions, maybe a Canonical Correlation might be useful for you, where you can have multiple dependent AND indenpendent variables. But see Tabachnick and Fidell (2007)- Using Multivariate Statistics, Chapter 12; or Cohen, Cohen, West and Aiken (2003) - Applied Multiple Regression/Correlation Analysis, Chapter 16. The latter book is also very useful for the inclusion of categorical predictors in your model. Both have also chapters about logistic regression (chapter 10 and 13, respectively)

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