DAPR2: Assessed Coursework Report
We are here to help and to clarify anything we can, however we will not answer direct questions such as “Is this [part of my coursework] correct?”
What we would like you to do is think about why you are asking the question. If it is because you are unsure about a section of the material, look back over it, come and discuss the examples from class, and then apply that to the coursework.
Please ask questions on the discussion forum so that all students may benefit from the answer (please also check that your question has not already been posted!)
Your task is to describe and analyse the data provided in order to answers a set of research question(s). Analyses will draw on the methodologies we have discussed in lectures and labs. The specific study contexts and research questions can be found in below.
Your report should include three sections:
1. Analysis Strategy
In this section you should describe how you are going to address the research aim(s) of the study described. Note, you may not need as many analyses as there appear to be questions as some may use different pieces of information from the same analysis. The marking of this section will be based on the completeness of your descriptions of:
data cleaning and variable recoding
any descriptive statistics or visualizations you will use prior to running models
the analyses you undertook (description of the models)
how you will check your model (assumptions and diagnostics including the criteria you have used to evaluate each)
specifically what information from each model provides the answer to the questions including details of your ! levels and any required corrections
rationales for all choices
Your analysis strategy should not contain any results. Hint
A reader of your report should be able to more or less replicate your analyses without referring to your R code.
The results section should follow logically from your analysis strategy and present the results of all aspects of your approach. A typical structure would begin by presenting descriptive statistics and move on to inferential tests. Things to remember:
You should provide full interpretation of key results
Model assumption and diagnostic checks should be noted (where reference to both decision rules from the strategy, and figures in the appendix are acceptable).
3. Discussion (very brief)
The Discussion section should contain very brief (1-2 sentence) summary statements linking the formal results to each of the research questions. The marking of this section will be based on the coherence and accuracy of these statements. This should not contain repetition of detailed statistical results, but should refer to those presented in the analysis.
Assumption and Diagnostics Appendix
In addition to the above, you may include an assumption appendix. This section has no page limit. You may use this to present assumption and diagnostic plots.
You must still describe your assumption tests in your strategy, including how you will evaluate them
You must still summarise the results in the results section of the main report
You must refer accurately to the figures and tables labels presented in the appendix
The assumption appendix is only for assumption and diagnostic figures and results. Any results from your main models including in the appendix will not be marked.
Finally, you do not need to include an introduction to the study unless you feel it is helpful in writing your analysis strategy.
You are required to submit two files:
- a complete report knitted to PDF
- and the associated .Rmd file
Knitting to PDF
Please note that to knit to pdf, you should:
- Make sure the tinytex package is installed.
- Makes sure the ‘yaml’ (bit at the very top of your document) looks something like this:
title: "this is my report title" author: "B1234506"
output: bookdown::pdf_document2 ---
If you cannot knit to pdf, then try the following steps:
1) Knit to html file 2) Open your html in a web-browser (e.g. Chrome, Firefox) 3) Print to pdf (Ctrl+P, then choose to save to pdf) 4) Submit the pdf you just saved.
The focus of this report is on your ability to create reproducible results, implementing analyses to answer research questions and interpreting the results. However, we do require that the reports are neatly formatted and written clearly. Below are some pointers:
Figures and tables should be numbered and captioned, and referred to in the text; important statistical outcomes should be summarised in the text.
Reporting should be clear and consistent. If in doubt, follow APA 7th Edition guidelines. Your report should be a maximum of 4 sides when the default formatting and font settings within RStudio are used when knitting your file.
Code chunks should be hidden in the pdf produced by your rmd file. To tell RMarkdown to not show your code when knitting to HTML, add echo=FALSE next to the r that appears after the backticks (https://uoepsy.github.io//rmd-bootcamp/05-echoeval.html).
For a guide on writing in RMarkdown, please see the Rmd-bootcamp lessons at https://uoepsy.github.io//rmd-bootcamp/ (https://uoepsy.github.io//rmd-bootcamp/).
Please submit both files on-line via the Turnitin links on the LEARN page for DAPR2. There will be two links, clearly labelled, as the files need to be submitted individually. The submission links will be within the Assessments tab and will become available after you click on the “Own work declaration” link.
Please name your file using only your exam number. For instance, B123405.Rmd and B123405.pdf
Compiled reports will be assessed according to the following components, with the following weightings:
Analysis Strategy = 40% Results = 40%
Discussion = 10%
Writing and formatting = 10%
The overall mark will be rounded to the nearest value on the extended common marking scheme for Psychology
Full details of what should be contained in each section of the report will be discussed in class. Please refer back to those materials. Below is some general guidance to think about as you write your report.
Your compiled report should contain:
- Clear written details of the analysis conducted in order to answer the question, including transparency with regards to decisions made about the data prior to and during analysis.
- Results, in appropriate detail (for instance, a test statistic, standard error and p-value, not just one of these).
- Presentation of results where appropriate (in the form of tables or plots).
- Interpretation (in the form of written paragraphs referencing relevant parts of your results) leading to a conclusion regarding the question.
Data & Research Questions
Conduct and report on an analysis that addresses the research aims.
Method & Procedure
In the present study, 300 participants were led on a guided tour of a museum, the National Museum of Scotland, during which they were asked to view 40 particular objects. Participants were randomly allocated into three observation conditions where they were assigned to either photograph objects as a whole, photograph objects by zooming in on one part of it (i.e., partially photographed), or observe the object but to not photograph.
The next day, participants’ memory for the objects was assessed, where they were randomly allocated into two retrieval-cue conditions – name and photo. In both conditions, participants completed a memory test that consisted of the names of the 40 objects from the museum tour randomly intermixed with 10 names of other objects that were not part of the museum tour but that were objects participants could plausibly have seen in a museum setting.
After completing the memory test, all participants completed a questionnaire assessing individual’s personality on six different traits (Honest-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness), measured by the self-report HEXACO-60 questionnaire.
The researchers want to know whether, after accounting for differences in personality traits:
- do differences in recall scores between name and photo retrieval-cue conditions depend on observation condition.
- whether the difference in recall scores between name and photo retrieval-cue conditions differs between those who took a photo (of any type) and those who did not.
PID Participant Identifier
H Score on personality items assessing Honesty-Humility from the HEXACO-60 Measure
E Score on personality items assessing Emotionality from the HEXACO-60 Measure
X Score on personality items assessing eXtraversion from the HEXACO-60 Measure
A Score on personality items assessing Agreeableness from the HEXACO-60 Measure
C Score on personality items assessing Conscientiousness from the HEXACO-60 Measure
O Score on personality items assessing Openness to Experience from the HEXACO-60 Measure
observation_condition Observation Condition (look only = visually observed objects, partial photo = partially photographed objects, whole photo =
photographed objects as a whole)
recall_score Recall accurary scores on memory test of 50 objects (sum scored; 0- 50)
retrieval_cue Retrieval Cue Condition (name = name retrieval-cue condition, photo = photo retrieval-cue condition)