50 points
I can state without a doubt there is no assignment in this course that will make or break a student more than this assignment, so please complete this assignment carefully and thoughtfully. This assignment asks you to pick a topic about which you will develop a literature review and practice various statistical analyses. The only reason you are picking this topic is to provide you with context as you are doing your work. That is it. This assignment is NOT related to your dissertation topic. As the assignment’s primary instructions state, you must pick a topic that is constrained by the data. So what data are the instructions referring to?
In the first data screening assignment (Module 2: Data Screening Assignment), there is an SPSS file that includes several dozen variable measures with over 1,200 records. It is a huge dataset from which to work. You will be using this data to conduct the various analyses and screening exercises for the course, which will ultimately lead to presenting an analysis from this dataset on your poster presentation in Modules 7 (draft) and 8 (final).
Picking the variables. The dataset describes specific variables from which you must choose for the conduct of your coursework. Again, the variables must come from the course dataset. Currently (as of August 2021), the variable list includes:
AVAILABLE DEMOGRAPHICS INFORMATION
- Gender
- Age (This is a continuous variable)
- Race
- Attraction
- Education
- Employment
- Income
- Relationship Status
- Length
- Religion
AVAILABLE SCALES & SUBSCALES
Personality & Mental Health Scales – Be sure to report the variables you will use.
- IPIP-50
- Extroversion
- Agreeableness
- Conscientiousness
- Neuroticism
- Intellect/Imagination
- Depression, Anxiety, Stress Scale (DASS)
- Depression
- Anxiety
- Stress
- Experience of Shame Scale (ESS)
- Characterological Shame
- Behavioural Shame
- Bodily Shame
- ESS Total
- PROMIS – Anger
- UCLA Loneliness Scale (ULS8)
- Satisfaction with Life Scale (SWL)
Religiosity Scales
- Religious Commitment Inventory (RCI) – Personal
- Religious and Spiritual Struggles Scale (RSS)
- Doubt
- Meaning
- Moral Struggles
- Interpersonal Struggles
- Demonic Struggles
- Divine Struggles
- Total
- GOD 10 – God Image
- Cruel
- Distant
- Loving
- Spiritual Assessment Inventory (SAI)
- Awareness of God
- Instability with God
On the list are 10 demographic variables and 28 psychometric measures from which to select your study’s variables. If the list does not include a variable you want to use–too bad. You will not be able to use it. You must stick with these 38 variables. Keep in mind, these are just for practice. This is not your dissertation.
When selecting your variables, you must choose two qualitative variables, also known as categorical variables, and two quantitative variables, also known as continuous variables. It is important to know the difference.
| Categorical
Variables that take categories as their values, such as yes, no, blue, male, female, freshman, etc. |
Continuous
Variables that have values that represent a counted or measured quality |
||
| Nominal | Ordinal | Interval | Ratio |
| A nominal scale consists of a set of categories that have different names. Measurements on a nominal scale label and categorize observations, but do not make any quantitative distinctions between observations. E.g., teacher, principal, White, Hispanic, Black, etc. | An ordinal scale consists of a set of categories that are organized in an ordered sequence. Measurements on an ordinal scale rank observations in terms of size or magnitude. E.g., freshman, sophomore, junior, senior. Likert scale items. | An interval scale consists of ordered categories that are all intervals of exactly the same size. Equal differences between numbers on a scale reflect equal differences in magnitude. However, the zero point on an interval scale is arbitrary and does not indicate a zero amount of the variable being measured. E.g., Likert scale means or sums. | A ratio scale is an interval scale with the additional feature of an absolute zero point. With a ratio scale, ratios of numbers do reflect the magnitude. E.g., Reading scores, height. |
There are some “tricky” variables on the list. For example, the demographic variable of Income is not what it seems. The measure of income in the dataset is along the groups of <$10,000, $10,000-$19,999, $20,000-$29,999, $30,000-$39,999, etc. These types of lists are ordinal in nature; they are not continuous. What makes them ordinal is they are grouped values that have an order to them, but one cannot conduct any type of mathematical operation upon the respective groups. For example, when a participant reports their income as $30,000-$39,000, one does not know where within that group their income lies. Is it $30,312? Is it $38,783? You just do not know. All we know is they make more than someone in the $20,000-$29,999 group and less than someone in the $40,000-$49,999 group. That’s it. If you are unsure about how the variable is measured, open up the dataset using SPSS and look at the values for the variables.
A second “gotcha” in the dataset (when do get around to using it) is there are a few seemingly deceptive variables listed. If you selected the DASS-Depression variable, which is common, then be sure to use the DASS-Depression variable. Do not use the DASS-Depression Categories variable that is listed in the data set. It is a categorical variable that counts how many participants are in each grouping. It is not what you want. Again, it is important to pay attention to your variables.
On a related topic, I have reviewed literally thousands of doctoral student proposals and dissertations, and I can generally tell how well designed a study is based upon how the variables are selected, defined, and described. A document in which the variables have been clearly defined and in which I can tell the student understands those variables is generally going to have a well-designed study. On the other hand, if the variables are vague or ill-defined, there is trouble on the horizon. The moral to the story is to make sure you clearly understand the nature of your variables.
Picking the topic
Ordinarily, one picks the topic before one picks the variables. However, for a course assignment, such as this, I suggest picking the variables first. Once you have picked variables that meet the criteria established, you can then pick a topic that conforms to these variables. For example, I will select the following variables:
- Gender (a categorical variable with a nominal level of measurement)
- Race (a categorical variable with a nominal level of measurement)
- Depression, as measured by DASS-Depression (a continuous variable with interval level of measurement)
- Neuroticism, as measured by IPIP-50 (a continuous variable with interval level of measurement)
You will notice my selection includes the name of the variable, the instrument by which is was measured, and the level of measurement. Identifying all three of these components will assist you in correctly conducting the data screening and data analyses.
Now my variables are selected, I can develop a topic around these variables. I could choose a topic, such as:
The relationship between neuroticism and depression as moderated by gender or race amongst doctoral students.
It does not (and should not) be more complex than that.
Selecting references
To support your topic, you will need to include at least four references from the extant literature. I suggest searching for articles based upon the variable names (e.g., neuroticism and depression). Skim the articles to make sure they are relevant to your topic, and then record the citation. Be sure the citation is correctly formatted according to APA Publication Manual 7th edition.
Submitting the assignment
I have included a lot of discussion for this assignment and, hopefully, you see why. You will be using these variables over and over and over again as you complete the course assignments, and the topic you select will guide the literature review assignments developing the need for further research.
When you submit the assignment, which must be a Microsoft Word document, you must have three elements clearly identified: the topic, the variables, and the references. A submission might appear as follows:
Topic
The relationship between neuroticism and depression as moderated by gender or race amongst doctoral students.
Variables
* Gender (a categorical variable with a nominal level of measurement)
* Race (a categorical variable with a nominal level of measurement)
* Depression, as measured by DASS-Depression (a continuous variable with interval level of measurement)
* Neuroticism, as measured by IPIP-50 (a continuous variable with interval level of measurement)
References
Barnhofer, T., & Chittka, T. (2010). Cognitive reactivity mediates the relationship between neuroticism and depression. Behaviour Research and Therapy, 48(4), 275-281. https://doi.org/10.1016/j.brat.2009.12.005
Fanous, A., Gardner, C. O., Prescott, C. A., Cancro, R., & Kendler, K. S. (2002). Neuroticism, major depression and gender: a population-based twin study. Psychological Medicine, 32(4), 719-728. https://doi.org/10.1017/S003329170200541X
Resnik, P., Garron, A., & Resnik, R. (2013, October). Using topic modeling to improve prediction of neuroticism and depression in college students. In Proceedings of the 2013 conference on empirical methods in natural language processing (pp. 1348-1353). https://aclanthology.org/D13-1133.pdf
Yoon, K. L., Maltby, J., & Joormann, J. (2013). A pathway from neuroticism to depression: examining the role of emotion regulation. Anxiety, Stress & Coping, 26(5), 558-572. https://doi.org/10.1080/10615806.2012.734810