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日期：2022-08-02 02:59

7PAVMALM – Multilevel and Longitudinal Modelling

Summative coursework assignment

2022 Resit assignment

Assignment summary

You have been provided with a labelled dataset containing a subset from an original study. Your task

is to undertake a theoretically and empirically meaningful analysis that requires the fitting of a series

of multilevel and longitudinal models.

The total amount of marks for this resit assignment is 60.

The final mark will contribute 70% towards the total mark of the module.

Background to the SOCRATES dataset:

The SOCrATES Trial – a Study of Cognitive Alignment Therapy in Early Schizophrenia.

This randomised controlled trial compared a 5-week CBT programme plus routine care to supportive

counselling plus routine care and routine care alone in a multi-centre trial randomising 315 people

with DSM–IV diagnosed schizophrenia and related disorders in their first or second acute admission

(Lewis et al, 2002; https://doi.org/10.1192/bjp.181.43.s91). There were 6 post-randomisation

exclusions, so the final dataset contains 309 people.

The primary outcome of the trial is the Positive and Negative Syndrome Scale (PANSS), a continous

measure of symptom severity ranging from 30-210, where a higher score indicates more severe

symptoms. A score of less than 70 indicates that a person is considered in remission, and a

secondary binary outcome records if a person’s score is less than 70 or 70 or more.

For the purposes of this assignment, the two intervention arms have been combined, and are to be

compared to the routine care alone arm.

The variables and their labels that are included in the dataset are:

idnumber Patient no#

therapy Therapy condition

interven Intervention or control

centre Centre

sex Sex

episode Admission episode

yearsofe Years of education

substmis Substance misuse

dup Duration untreated psychosis: weeks

logdup log10dup

ageentr Age at entry to study: years

panss0 Baseline panss total

panss1 Six week panns total

panss3 3 mnth panss total

panss9 9 mnth panss total

panss18 18 mnth panss total

therapis Therapist identifier

nosess Number of therapy sessions

panss0remis PANSS remission at baseline

panss1remis PANSS remission at 6 weeks

panss3remis PANSS remission at 3 months

panss9remis PANSS remission at 9 months

panss18remis PANSS remission at 18 months

Assignment details

For this assessment, consider the questions presented below and try and answer them. You should

discuss what you found and not simply reprint output from Stata. Remember to justify your choice of

statistical models and approach to the analysis.

1) Include a front sheet with your student number. Do not put your name anywhere on the

submission. Please include the word count per question, where this is specified. Tables and

figures do not count towards the word limit.

2) Present properly labelled tables, and make sure that the tables and figures are standalone

with captions describing their contents.

3) Give detail about the methods chosen for analyses and any alternative choices that could have

been considered, more so than in standard research reports.

4) At the end of the report, include your labelled do file (you can copy and paste it in word) with

the commands you have used to carry out the analyses.

5) Your answers may include a combination of text, tables and/or figures. Choose the most

appropriate way to present the findings.

6) Maximum 3000 words (excluding tables/ figures/do file) and upto 5 figures/tables.

Questions

1. Summarise the binary outcome variable (PANSS remission) between the combined

intervention arm and routine care alone arm over time.

Note: you could use graphs or tables to display these.

[5 marks]

2. Using an appropriate generalised linear mixed model, estimate the treatment effect

of the combined intervention arm to routine care alone on the PANSS remission

outcome at 9 months. You should check the robustness of your results by

performing suitable sensitivity analyses, and describe in statistical terms the methods

chosen for analyses and any alternative choices that could have been considered.

[15 marks]

You should consider the following:

An appropriate longitudinal model, based on scaling of the time variable

The appropriate metric to report the treatment effect

Any additional sources of clustering in the data

An appropriate random effect structure, based on model comparisons

Choice of any baseline variables to include in the model

Validity of underlying statistical assumptions

Graphical displays to summarise the findings from the modelling

3. Using a Generalised Estimating Equations approach, estimate the treatment effect of

the combined intervention arm to routine care alone on the PANSS remission

outcome. You should check the robustness of your results by performing suitable

sensitivity analyses, and describe in statistical terms the methods chosen for analyses and

any alternative choices that could have been considered.

[15 marks]

You should consider the following:

An appropriate correlation matrix, based on scaling of the time variable

The appropriate metric to report the treatment effect

Choice of any baseline variables to include in the model

Validity of underlying statistical assumptions

Graphical displays to summarise the findings from the modelling

4. Using a Generalised Estimating Equations approach, estimate the treatment effect of

the combined intervention arm to routine care alone on the continuous PANSS

outcome. You should check the robustness of your results by performing suitable

sensitivity analyses, and describe in statistical terms the methods chosen for analyses and

any alternative choices that could have been considered.

[15 marks]

You should consider the following:

An appropriate correlation matrix, based on scaling of the time variable

Choice of any baseline variables to include in the model

Validity of underlying statistical assumptions

Graphical displays to summarise the findings from the modelling

5. Summarise your findings from questions 2, 3, and 4 in the form of a research report

abstract results section. You may wish to highlight the difference between marginal

and conditional effects, and which of your analyses correspond to these.

[5 marks]

6. Include your STATA do or log file. This should follow good programming standards

(header/commented throughout). The log file should be error free and the do file

should be able to replicate your findings

[5 marks]