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APSY-UE-1137 Research Methods in Applied Psychology II Lab Assignment #1
发布时间：2024-06-14
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Research Methods in Applied Psychology II
APSY-UE-1137
Lab Assignment #1
For steps 1 through 3 of this assignment, use the data set titled “lab1assignment.sav” (located on NYU Brightspace). Make sure to clearly label your responses. To address the hypothetical argument presented below, analyze the factor structure and establish the reliability of the Affect Scale, following steps 1 through 3. Please read the instructions and notes carefully, and attach the requested outputs and syntax in your word file.
Historically, psychology has conceptualized affect as the manifestation of an emotional response by a person to his or her environment. Researchers have separated affect into two broad types, positive and negative.
However, there have been an increasing number of debates in the literature as to whether affect is one underlying dimension or has multiple underlying dimensions. If it’s one dimension, people’s affective state is hypothesized to exist on a continuum with positive and negative end points. In contrast, the multidimensional view holds that affect may be better represented as two (or more) distinct constructs.
In this lab assignment, you will evaluate the underlying structure of affect using data collected using the Positive and Negative Affect Schedule - Expanded Form (PANAS-X) scale (posted on NYU Brightspace). This scale consists of a number of words and phrases that describe different feelings and emotions. Participants were asked to read each item and then indicate to what extent they have felt this way during the past few weeks on the following response scale:
very slightly a little moderately quite a bit extremely
1 2 3 4 5
To test this, run an exploratory factor analysis (EFA) on the data set “lab1assignment.sav” . Be sure to include all 12 items of the scale, and use maximum likelihood extraction with direct oblimin (oblique) rotation.
Step 1.
a) Attach all syntax and the following SPSS output from your analysis: “Total Variance Explained” Table and “Scree plot” Figure. (5 pts)
b) Based on the total variance explained, eigenvalue and scree plot, decide how many factors to interpret. Using the output, explain why you chose to retain that number of factors. Be sure to state the proportion of variance explained by each factor, their eigenvalues, and describe the shape of the scree plot to receive all points. (10 pts)
Step 2.
a) Attach all syntax and the following SPSS output from your analysis: “Structure Matrix” Table and “Factor Correlation Matrix” Table. (5 pts)
b) Use the “Structure Matrix” Table to identify the items that load highly on each factor. Using these loadings and your own conceptual judgment, name (i.e., come up with a label) each of the factors you have retained. Then, briefly describe what is captured by each factor you identified (e.g., why you chose that name, the key construct the items tap into). Make sure you write down the number of items that loaded on to each factor, as well as the label for each individual item (e.g., “upset”). (20 pts)
c) Identify items that double-loaded onto more than one factor and make a decision about keeping or removing the item(s). Explain your choice by describing whether you kept them as items in one factor or another, or did not keep them at all. Explain why you made this decision. (15 pts)
d) Describe the correlations between the factors. Make sure you report the correlation values for each pair of factors. Describe whether you think the factors are unique or redundant. (15 pts)
e) There have been an increasing number of debates in the literature as to whether affect is one underlying dimension or has multiple underlying dimensions. If it’s one dimension, people’s affective state is hypothesized to exist on a continuum with positive and negative end points. In contrast, the multidimensional view holds that affect may be better represented as two (or more) distinct constructs. Describe what you have learned about the nature of affect as assessed by this scale. What do your results for the EFA suggest about how best to conceptualize affect? (10 pts)
Step 3.
a. Imagine that you are to create a scale out of the items that load highly onto Factor 2 (i.e., above 0.4). Examine the dataset to see if any of the high-loading items on Factor 2 need to be re-coded before averaging the items to create a scale representing that factor. Explain how you know whether any reverse coding is needed. If there are any, state which ones they are. (4 pts)
b. Run an inter-item reliability analysis using Cronbach’s Alpha reliability test for the highly-loaded items on Factor 2. Evaluate whether the alpha can be improved by dropping any items. Describe what would happen if any items are dropped in the scale. Then report and interpret the highest Cronbach’s Alpha. Copy and paste the SPSS syntax and output. (10 pts)
c. Now, actually create the scale score for the items highly-loaded onto Factor 2. Once you have created this new variable, run descriptive statistics (Analyze > Descriptives statistics) to get the mean and standard deviation. Copy and paste the SPSS syntax for the scale score calculation and the SPSS syntax and output for the descriptive statistics below. (6 pts)
