On Sun, 11 Oct 2020 13:45:47 -0400, Rich Ulrich

*Post by Rich Ulrich*On Sun, 11 Oct 2020 06:23:15 -0700 (PDT), Eshani Sandali

*Post by Eshani Sandali*When computing the variables, should i keep the

values for the computed variables as same as values

that have been added for the individual questions?

(EX= 1= strongly disagree..) and what should be

the measure of computed variable?

Sorry. I can't make sense of the question(s). Computing

what variables? And what is meant by "values ... added"?

If you want to get the Predicted value for each case in

a multiple regression, request it as an option.

** Here is the response from Eshani, mistakenly sent to my

email address **

<< I have selected five independent variables namely, perceived

usefulness, ease of use, risk, trust and awareness. For each of the

dimensions i created five questions. When doing the multiple

regression i have to compute the five questions so that i can get a

one computed variable called Perceived usefulness and in the same

way for other variables as well. In that computed variable, the mean

value can be a in between value. So before running the multiple

regression do i have to round off them or keep it the way as the

results produced? >>

Creating "composite" or "factor" scores for each of the sets of

items is a great idea. Some people have used Total scores; I

prefer using the Average scores for test items, because using

the Means keep visible the verbal anchors for the scores.

There is absolutely no reason to truncate or round off the

item averages before using MR.

The one circumstance where I routinely round off variables

is: after computing "T-scores" -- I create those as composite

scores averaged from multiple factors, and standardized to have

a mean of 50 and SD of 10. I round them off (a) because

there is going to be essentially no loss of precision and (b)

so that I can list scores without decimals, or I can point to

individual scores and not worry about two scores that "look

the same" being different by a trivial fraction.

--

Rich Ulrich