SPSS TIPS Flashcards
DATA FILES
Always ensure variables are clearly named and labelled. (names are up to 8 characters only for PROCESS), so may as well stick to this throughout spss.
Always ensure value labels have been added.
Always ensure computed/recoded variables are clearly defined.
Always make sure the variables and labels etc are easy for you to work with, and remeber others in your absence need to be able to work with the file also.
NOTEPAD
There is a notepad fn under
>Utilities
>Data file comments
It is helpful to add notes here re what have done to your file and save it. It will get date stamped and saved as part of the data file. Helpful for you and others to keep track.
Make sure to TICK for > Display comments in output.
DATA FILE ORGANISATION
Name variable by scale and subscale for ease of identification. Be as specific as can be for variable names. Make sure you can readily recognise which variables you need without having to refer to your Q all the time.
eg. Depression Anxiety Stress Scales (DASS). Label questions according to both questionaire and subscale (each q will be a variable)
egDASS_1_5,DASS_2_A
eg DASS_3_D,DASS_4_A etc.
D=Depression subscale, 3 refers to q 3 etc. Use undersores as cannot have spaces in variable names.
MISSING VALUES CODE
In the Missing box, it will default to none. But if you want to label missing data as a value, can change this by
> Discrete Missing Values. eg type in 97, 98, 99.
(The other option to label lissing data is Range, but this is only used if labelling a large amount of missing data, which hopefully you never have)
Dr J finds it handy to use codes 97=illegible answer
98=skipped answer or Not applicable
99= did not answer.
RECODING
If recode into > Same Variable, it overwrites the old variable, whereas if REcode into> Different Variable, it creates a new variable and keeps the original (safer but either is fine as long as know what are doing).
> Transform
> Recodeinto Different Variables
Note Input Variable is your original variable. Output variable is the new variable you are creating. Give it a meaningful name.
eg Recodings;
1. Reverse scoring. Single code for single replacement
2. Collapsing of categories ie make use of Range options to note a range of scores which should be collapsed into a single score/code. eg create age bands from a continuous age variable. eg. create a never/ever variable from a behaviour frequency variable.
FILTERING OUT PARTICIPANTS
filtering out participants;
>Data
>Select cases ie select cases to KEEP. Can Delete out others or just Filter out others (unselected cases). If dDelete out, SAVE data file as NEW DATA SET. A Filter allows you to remove participants but they are just hidden from view. to bring them back;
>Data
>Select cases
>select All cases.
For filtering, choosing which ones to Keep. eg the formula variable >X will keep those scores above X value and filter out those below.
SYNTAX SAVING AND ANNOTATION
Anytime you run an analysis, you have option to ;
> OK or >Paste
Paste brings up syntax. Can also annotae in the syntax, just *at start of row typing and this will record your notes without thinking it is a computer command. Paste is always recommended. Then Hit Play to run the Analysis.
Hierarchical Regression
The “Hierarchical module” in spss does NOT do the correct Hierachical Regression. Spss will add in 1 variable at a time or blocks of them and tell a regression analysis, but the table will have multiple slabs reflecting what happens at each block. Each block is interpreted as adding whatever is in that block to whatever was in all the preceding blocks. BUT use PROCESS MACROS TO do a hierarchical or sequential model, you put a variable, or block of variables, in first and it will provide you with up-to-date data. When you add further variables, the data updates to what is changing.
PROCESS MACRO
select model 4 for simple regression.(multiple mediation)
X=predictor
Y=d/v or outcome
med1, med2,med3 etc=mediators
5000 is the default for how many re-samples the computer takes.
Under OPTIONS,
-select “to get total effect” (total effect is direct plus indirect effects)(which is c)
-tick if want to have effect size
-usually no centreing required for mediation
process macro 2
process macro 3
process macro4
Note in this pic, the confidence intervals are both negative, and this means that zero is not included in the range, and therefore, it is significant.
Process macro-putting it all together
Have gotten all the numbers from the various outputs, and can slot them into the total model.
