Compute Variables and Analyses

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MonkeyStudent
Posts: 2
Joined: Tue Jan 03, 2017 10:41 am

Compute Variables and Analyses

Postby MonkeyStudent » Tue Jan 03, 2017 10:57 am

Hey,

I'll try to explain it step by step. In my study, i have asked on a 10-point scale what the respondents think about the wrongfulness of 11 different crimes for which i have 11 different variables in SPSS. I need to make a scale so i have computed them (MEAN and SUM). I want to see if there is a difference between two groups for which i have chosen the Independent t-test.

Question 1: Should i use the computed MEAN or SUM scores of the variables in an independent t-test? Which give a more clear (better) output?

Question 2:Same question for when using (single and multiple) regression analyses

Thank you in advance
statman
Administrator
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Joined: Tue Jun 12, 2007 12:08 pm
Location: Florida, USA

Re: Compute Variables and Analyses

Postby statman » Tue Jan 03, 2017 1:09 pm

If understand, load in the raw Likert date but make sure you define the variables as Ordinal

Also .............
See the note below

NOTE: Please read the Posting Guidelines and always tell us your OS, the SPSS version and information about your study and data!

Statman
Statistical Services
MonkeyStudent
Posts: 2
Joined: Tue Jan 03, 2017 10:41 am

Re: Compute Variables and Analyses

Postby MonkeyStudent » Tue Jan 03, 2017 3:49 pm

My guidance counciller said i had to make scales to avoid Type I errors, because i have allot of variables. I need to know if there is a difference between Gamers and NonGamers for their perception towards the wrongfulness of crimes.
He is on holiday vacation now for another week, so i was wondering if he meant by 'scaling', that i need to compute my variables. If so, my original question is: what output should i interpret, SUM or MEAN scores of the computed variable to present the data in my paper.

I use a laptop with Windows 10, 64bit; SPSS Version 24

What i have done is the following:
Raw data/Variables
Var3.2.1 = Breaking in a home without violence
- Values: 1=1, 2=2, 3=3,... 10=10, 999=not filled in
- Measurement level: Ordinal
Var3.2.2 = Stealing with violence
- Values: 1=1,...
- Measurement level: Ordinal
....
Var3.2.11=Discrimination
- Values: 1=1,...
- Measurement level: Ordinal

Compute
SUM (Var3.2.1,Var3.2.2,Var3.2.3,Var3.2.4,Var3.2.5,Var3.2.6,Var3.2.7,Var3.2.8,Var3.2.9,Var3.2.10,Var3.2.11)
- Variable name= Wrongfulness_SUM
- Measurement level: Scale

MEAN (Var3.2.1,Var3.2.2,Var3.2.3,Var3.2.4,Var3.2.5,Var3.2.6,Var3.2.7,Var3.2.8,Var3.2.9,Var3.2.10,Var3.2.11)
- Variable name= Wrongfulness_MEAN
- Measurement level: Scale

Test for analysis
Independent T-test
- Test Variables
==> Wrongfulness_MEAN
-Measurement level: Scale
==> Wrongfulness_SUM
- Measurement level: Scale
- Groupung Variable
==> Not_Gamers (NG; defined as '0')
- Measurement level: Nominal
==> Gamers (G; defined as '1')
- Measurement level: Nominal

Output
Wrongfulness_SUM & Wrongfulness_MEAN:
http://imgur.com/a/y6ByZ#WyozJc7

Apologies for the imgur link (lacking skills in img posting on forum)

Question 1: Is this the right proces for scaling 11 variables to 1 variable?
Question 2: What output data should i interpret?

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