Question 1
In the data output you can see that a range of demographic, clinical and psychological characteristics of the sample were recorded (e. g., gender, age, marital status, education, living status, personal and family income, ethnicity etc) across both the schizophrenia cohort and non-psychiatric comparison group. Present the demographics in a table.
Check for differences across groups by comparing characteristics where appropriate.
If appropriate check for differences across groups by comparing characteristics where appropriate. Remember to describe any transformations you performed on the data, the tests you used to analyse your data and explain why these tests were appropriate.
Question 2
Schizophrenia is associated with positive symptoms (e.g. delusions, hallucinations) negative symptoms (e.g. anhedonia, lack of motivation) and cognitive symptoms (e.g. problems with learning and memory).
How do positive symptoms (measured using the Scale for the Assessment of Positive Symptoms; SAPS) and negative symptoms (measured using the Scale for the Assessment of Negative Symptoms; SANS) relate to one another in the whole sample and in those with schizophrenia only? Could the relationship between SAPS and SANS in the schizophrenia cohort be attributed to differences in executive function (Executive Functioning Composite Score)?
Remember to check your data for assumptions of the tests and things like outliers. Describe any transformations you performed on the data, the tests you used to analyse your data and explain why these tests were appropriate.
Question 3
Is it possible to predict total loneliness score based on Anxiety, Depression and Stress in the whole sample? How about only with those with schizophrenia?
Note that the total loneliness score is not included in the data - you will need to calculate this yourself. Importantly, variables uclals01, uclals05, uclals06, uclals09, uclals10, uclals15, uclals16, uclals19, uclals20 should be reverse coded.
Provide summary output describing the coefficients associated with each variable and their respective t and p values. How well does your model predict loneliness in the non-psychiatric comparison subjects (note, for this it is worth being aware of the predict() function here)?
Remember to check your data for assumptions of the tests and things like outliers. Describe any transformations you performed on the data, the tests you used to analyse your data and explain why these tests were appropriate.
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