Examine the data file for any missing values or errors.
The primary theme of the paper is Examine the data file for any missing values or errors. in which you are required to emphasize its aspects in detail. The cost of the paper starts from $79 and it has been purchased and rated 4.9 points on the scale of 5 points by the students. To gain deeper insights into the paper and achieve fresh information, kindly contact our support.
Advanced Research Methods 1: Coursework guidelines
Assessment one of this module involves performing analyses on a data file (provided) and producing a report of the findings. The data will be located on blackboard from week two. It is advised that you read through this information before you commence any calculations in SPSS.
It is a good idea to familiarise yourself with the variables involved and consider how they may differ and/or relate to each other. Read the description/question in each section and be familiar with the appropriate SPSS procedure you will need to conduct.
From week three onwards, you should be able to start working on preparing the data for analysis. As the module progresses you will be in a position to conduct further analysis.
Marks will be allocated on the basis of correct interpretation of findings and insightful and/or novel further comment (e.g. reference to implications).
Presenting the results:
- Do structure the report into sections (see also the marking grid)
- Briefly introduce each section of the report e.g. the objective of the section and (briefly) what will be presented
- It is recommended that you use parametric tests wherever possible
- Do review module handouts for recommendations on how best to present and report findings
- Use tables for descriptive information. Line graphs may be presented to illustrate significant interaction effects (section 4)
- Interpret your results with relevant statistical information and give some indication of relevance of findings
- When interpreting findings, do draw attention to the ‘direction’ of results where appropriate
- Please do not copy and paste tables from SPSS. Graphs may be copied but adjusted to a more suitable size
- Please label all tables and graphs appropriately (i.e. tables, figures)
- Inclusion of a reference section is recommended
- Do make a back up copy of the original data set
- You may find it helpful to keep a syntax file of your analyses
Writing up the report should be completed independently. It is probable that you will have discussed the work with student colleagues however you must ensure that you are the sole author of the entire document that is submitted.
A local NHS smoking cessation clinic has conducted a study where a number of smokers have been questioned. The clinic has tasked you with analysing data and to write up a report based on findings. The data has been collected from 116 participants (including some University students) that smoke who were asked about variables related to their smoking (e.g. intention to stop smoking, health value). There are 28 variables with information about demographic factors, ratings on visual analogue scales (perceived risk, self efficacy, subjective norms and intentions to stop smoking), information on previous smoking related illnesses, health value ratings and 18 items from a reliable and valid questionnaire.
The data file has been named ‘Smoking study 2016’ and consists of:
ID – participant number
Participant Sex (Male/Female)
Age (open responses in years)
Accom – type of living accommodation (own home, family home, student accommodation)
Cignum – number of reported cigarettes per day
Illness – perceived smoking related illness ever (yes/no). This may include acute infectious illnesses that may not have been formally diagnosed as being smoking related
Ratings from Visual analogue scales (from 0-100):
Risk – perceived risk of smoking related illness/disease (higher ratings = greater perceived risk)
Intent – intentions to stop smoking in the future (the higher the score = the higher the perceived intention to stop smoking)
Selfeff – self efficacy to stop smoking (higher scores = stronger self efficacy)
Norm – subjective norms for stopping smoking (higher scores = more significance given to feelings/desires of significant others)
Feelings about own health:
Value – Health Value Scale (Lau, Hartman & Ware, 1986). Four items measured participant feelings about their own health (higher ratings = greater value attached to personal health)
MHLC1 – MHLC18 – are the 18 items from the Multidimensional health locus of control scale (MHLC) (Wallston, 1978). Each item is rated from 1 (strongly disagree) to 6 (strongly agree). Scoring details were given in week 2.
Preliminary data screening
Prior to your main analyses:
- Examine the data file for any missing values or errors.
- Compute three new variables to represent as per the MHLC scoring guidelines. You should report and comment on the internal reliability of these scales.
- The NHS smoking clinic are interested in responses from different age groups. Transform your raw scores of ‘age’ into a new variable to reflect which age group your participants belong to (see next point).
- It has been suggested that you divide your participants into one of three age groups (either: 18-21, 22-24 and 25-40). Assess the frequencies of the raw scores of age to check these proposed groupings offer a relatively equal proportion of participants in each of the suggested age groups.
- Give each of the new variables meaningful labels and add ‘value labels’ to your three age groups.
- Write a short commentary to introduce the report. Make reference to the aims of the document outline/summarise the contents of the data and any prominent questionnaires/measures. Outline what has been done with the data prior to statistical analysis (i.e. the steps conducted here).
The smoking clinic has asked you to summarise demographic information for participants that were recruited to the study. This should include demographic information for participants in addition to descriptive detail for the number of reported cigarettes smoked per day. You should also provide some comment on any interesting or unexpected findings.
The clinic are interested in group differences on visual analogue scale (VAS) measures and the health value scale according to whether participants have reported they had (perceived) a smoking related illness or not.
- Present a table of appropriate descriptive statistics.
- Key inferential statistical information can be appended to the table of descriptives.
- Provide a brief commentary on what you have presented summarising the findings in an appropriate way. Please also consider equality of variances in your findings.
- Briefly consider some implications of these findings.
The smoking clinic is also interested in any possible association between gender and smoking related illness as well as smoking related illness and type of participant accommodation.
- Present relevant descriptive information in table format.
- Provide a brief commentary/summary of the findings using appropriate statistical information.
- Do briefly consider any implications of your findings.
Staff at the clinic have theorised that there will be effects of both age group and sex on selected measures. The clinic is interested in determining how these two factors influence subjective norms and the scales of the MHLC.
- Present a table of appropriate descriptive statistics for each scale.
- Do also consider/comment on equality of variances for each test.
- Line graph(s) will be beneficial to illustrate any significant interactions.
- It is requested if you detect significant effects of age group, you should perform a suitable additional test to assist in interpreting these findings.
- Provide a commentary/summary of findings and consider the direction of any significant differences.
- Consider some of the possible implications of these findings.
There are two parts to this section. Firstly, additional analysis should be performed on data and second, you will need to consider some key aspects of what has been found throughout the report.
The clinic has asked for your advice in performing further analysis on the study data. You are therefore free to conduct any further (possibly exploratory) statistical analysis that has (preferably) been covered on this module.
Consider what question(s) you could ask about this data, e.g. what could you explore that has not already been examined here? Maybe you could explore something using a different analytical procedure to what has been done so far?
Please present results in an appropriate format (e.g. table and a commentary citing relevant statistical information). There is scope to consider any implications or interesting/contradictory findings here.
The smoking clinic has requested that you give some consideration to some of the key findings presented (i.e. from each section). It is recommended you give some suggestions for further research and any recommendations you may have to the clinic based on what you have found (e.g. implications for smoking cessation intervention development). Do refer back to previous sections or tables/graphs in the report if necessary.
There may also be relevant links that could be made with material covered on other modules or previous studies that you know of.