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Posted: December 20th, 2022

Measurement and Assessment (M&A) II Assignment

Psychometric analyses in SPSS,

Measurement and Assessment (M&A) II Assignment
1 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
Measurement and Assessment (M&A) II Assignment
This M&A II assignment consists of carrying out psychometric analyses in SPSS, and reporting the
results. This is an individual assignment, so you are required to do the analyses and write the
research report by yourself. The research report should be comprehensible for people who are not
familiar with the details of psychometric analyses.
Below the required analyses are detailed. You can do all these analyses in SPSS. In reporting the
results, you can copy-and-paste SPSS tables, if you like, but tables should include your own table
caption (titles) and table number and you should remove non-relevant information from the tables.
The report should include clear statements on the reason for the analyses (what are the research
questions?) and the meaning of the results (what are the answers to the questions?).
Word limit
The word limit is 1600 words (not including tables).
Writing and plagiarism checking
The report should be written in clear and correct English. Make sure your report contains no spelling
or grammatical errors (please run a spelling check). Assignments with too many spelling or
grammatical errors will not be graded. You are required to do this assignment individually and to
write the report individually. Note: all reports will be submitted to a rigorous plagiarism checker.
Relationship to lectures and literature
This assignment relates directly to
Furr chapters: 4 (exploratory factor analysis)
Workbook chapters: 2 (logistic regression), 3 (factor analysis)
The relevant PowerPoints: Week 2 Lecture 1, Week 2 Lecture 2, Week 3 Lecture 1
Schedule
When To do Who?
Friday 4 Nov 2022 Assignment on Canvas (rubrics will follow
shortly) Dirk Pelt
Sunday 27 Nov 2022 Hand in first version before 23:59 Students
Wednesday 14 december Feedback before 23:59 Tutors
Friday 23 Dec 2022 Hand in final version 23:59 Students
Sunday 22 Jan 2023 Give end grade before 23:59 Tutors
2 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
Assignment: Neuroticism, Agreeableness & problematic smartphone use
In a pilot study on the psychological consequences of problematic smartphone use among young
adults, a short personality questionnaire was administered to a sample of N=259 participants
between 17 and 24 years. The test measures the personality traits Neuroticism and Agreeableness
by means of 10 Neuroticism and 10 Agreeableness items. In addition, a close acquaintance of each
participant was asked to rate their problematic smartphone use (PSU) by responding to the question
“Does he/she spend too much time on their phone?” (coded 0=no, 1=yes). This variable is called PSU.
The aim of the pilot study was to determine whether:
1) the intended latent factors Neuroticism and Agreeableness are found in the data;
2) the psychometric quality of the personality questionnaire is sufficient;
3) Neuroticism and Agreeableness predict the variable PSU.
The data. The sample comprises 259 young males and females between 17 and 24 years. The 10
Neuroticism items are labelled N1 through N10, the 10 Agreeableness items are labelled A1 through
A10. The actual items, i.e., the content, can be found in the variable labels (e.g., item N5 reads “I
rarely get irritated”). The response format is a 5 point scale, with score 1 indicating “disagree
completely” and 5 indicating “agree completely”. A higher score indicates a greater degree of
Neuroticism or Agreeableness. In addition, as mentioned above, there is the dichotomous variable
PSU (0 means “no problematic smartphone use” and 1 means “problematic smartphone use”). The
SPSS system file containing the data is called NeurAgreePSU.sav.
Note. Some items were negatively formulated, meaning that agreeing with an item actually meant a
lower score on the trait. However, these items have already been reverse scored, so when you
calculate sum scores (see below), you can just add up all the item scores.
The analyses (SPSS menu navigation is discussed below). The present aim is threefold.
The first two aims are investigating whether the intended two-factor structure is found and to assess
the psychometric quality of the items:
Dimensionality & Item quality. Carry out a factor analysis on the 20 Neuroticism and Agreeableness
items.
1. Fit the two common factor model to the data using the maximum likelihood method using
oblique rotation. Investigate the factor loadings (i.e., in the Pattern matrix). You will see that
there are two items (one Neuroticism item and one Agreeableness item) that can be considered
problematic. Identify these two items, and repeat the factor analysis without these two items.
Hint. Recall from Workbook CH3 that: “in general the items with a loading <.30 are
considered as items that do not fit well within the set of questions, the questionnaire, or the
factor.” Also, an item can be considered problematic if it loads higher on a factor other than
the one it is supposed to measure.
2. Interpret the scree plot and eigenvalues of the factor analysis based on the 18 remaining items.
Describe both rules of thumb for the number of factors to extract, and explain for each if the
rule of thumb is in line with an extraction of two factors. Either way, we will continue with the
extraction of two factors.
3. Report the factor loadings, the communalities, and the factor correlation.
3 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
The third aim is to analyze the relationship between personality and problematic smartphone use.
Logistic regression analysis. Determine whether Neuroticism and Agreeableness predict problematic
smartphone use (PSU). To this end, first calculate the test scores by summing the 9 Neuroticism
items into a single score and by summing the 9 Agreeableness items into a single score (so in the end
you have two sum scores). Calculate the z-scores of the test scores by standardizing the test scores.
Use the standardized variables as the predictors in the logistic regression analyses. Do the analysis
twice: once with the Neuroticism z-scores as the predictor, and once with the Agreeableness zscores as the predictor. Include in your report the relevant null hypotheses, and the alpha level of
0.05.
Do neuroticism and agreeableness predict the probability of problematic smartphone use (PSU=1)?
If so, evaluate only for the variable(s) that significantly predict PSU the(ir) predictive value. Do this as
follows:
Calculate and report
1) the unconditional probability of PSU=1, and
2) the probability of PSU=1 given the mean of the z-scores (zero) and
3) the probability of PSU=1 given the mean plus one standard deviation of the z-scores. Because the
predictor is standardized, the mean equals zero and the mean plus 1 standard deviation equals
0+1=1. So in your discussion, include:
prob(PSU=1), i.e., the unconditional probability for PSU=1, and the following conditional
probabilities
prob(PSU =1|zscore=0) = 1 / (1 + exp(-(b0 + b1*0)) and
prob(PSU =1|zscore=1) = 1 / (1 + exp(-(b0 + b1*1)),
in other words, the conditional probabilities of PSU =1 given z-score = 0 (the mean) and z-score = 1
(the mean + 1 SD).
Discuss, based on (your subjective evaluation of) these probabilities, the strength of the predictive
value of each of the personality traits. Which of the two personality traits is a stronger predictor of
PSU? Can you come up with an idea for why one trait is a better predictor than the other? For a
refresher on the Big Five personality traits, see https://www.youtube.com/watch?v=IB1FVbo8TSs.
Report sections
Carry out the required analyses in SPSS (instructions are given below), and write a report on the
basis of the results. Your report should include:
1) Title page. Title page with a sensible title, your name and student number, and the word count
(make sure that the word count is < 1600).
2) Introduction. Introduction with research problem and the aims of the psychometric analyses.
3) Sample and variables. Brief description of the variables and the sample (including gender and
age). Provide descriptives (table 1 with means and standard deviations of the items and the
variables PSU, sex and age).
4) Method section. A method section in which the methods are discussed briefly – which analyses
are carried out (factor analysis and logistic regression analyses) and which questions do these
answer? In the case of the logistic regression analyses, mention the null hypotheses and the alpha
level of 0.05 (i.e., α=.05).
4 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
5) The results (2 tables and 1 figure).
5A) Describe results of the factor analyses (table 2 with rotated factor loadings and
communalities based on the 18 items). Include the scree plot (figure 1). Report the
correlations between the common factors in the text and interpret it.
The following questions need to be addresses in your report. First, looking at the content of
the items of the two items that you have removed from the questionnaire after the first
factor analysis, can you come up with a reason for why these items might not function so
well? Second, given that the questionnaire is supposed to measure the two latent variables
Neuroticism and Agreeableness, are the results interpretable as such? That is, is the
intended two-factor structure found in this dataset? Third, are the questionnaire items good
indicators for Neuroticism and Agreeableness?
5B) Describe the results of the logistic regression analyses (table 3 with the parameter
estimates, standard errors and p-values).
6) Conclusions. Conclusions with a clear answer to the question concerning the psychometric
characteristics of the test and the predictive value of the Neuroticism and Agreeableness scores. Is
the questionnaire acceptable in terms of interpretation of the factor structure and is the quality of
questionnaire items adequate? Do the personality traits predict the variable PSU? Rather than only
focusing on statistical significance also focus on predictive value, as expressed in terms of
conditional probabilities relative to unconditional probabilities (see above for explanation on this).
5 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
SPSS menu’s
The SPSS data file is called NeurAgreePSU.sav.
Factor analysis (workbook chapter 3)
Menu’s: Analyze, Dimension reduction, Factor
In the menu under “Extraction” choose the following options. Make sure to choose Maximum
likelihood.
In the menu under “Rotation”, choose “Direct Oblimin”.
6 M&D II / M&A II 2022-2023 Assignment
M&A II / M&D II 2022-2023. Individual assignment. English version
Sum scores and z scores.
To calculate the test scores (i.e., sum scores) based on the items scores, you can execute the
following syntax and fill in the item names in the open … spots (see workbook Chapter 2 Appendix:
Using SPSS syntax). Please note that a final dot (.) is needed after each statement.
COMPUTE Neuroticism = N1 + … + … + … + … + … + … + … + …. .
EXECUTE.
COMPUTE Agreeableness = A1 + … + … + … + … + … + … + … + …. .
EXECUTE.
You can obtain z-scores of the sum scores by choosing “Analyze” and “Descriptives”, and clicking on
the option Save standardized values as variables.
Logistic regression (workbook chapter 2)
Menu’s: Analyze, Regression, Binary logistic

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