Multiple Regression Analysis: Factors Affecting Individual's Daytime Sleepiness Level
QUANTITATIVE ANALYSIS REPORT: MULTIPLE REGRESSION ANALYSIS ASSIGNMENT INSTRUCTIONS
OVERVIEW
You will take part in several data analysis assignments in which you will develop a report using tables and figures from the IBM SPSS® output file of your results. Using the resources and readings provided, you will interpret these results and test the hypotheses and writeup these interpretations.
General Submission Guidelines:
• Copy and paste all tables and figures into a Word document and format the results in APA.
• Interpret your results.
• Final report should be formatted using APA style, and in a Word document.
• 4-5 double-spaced pages of content in length (not counting the title page or references).
This assignment has two parts:
a. Complete the Additional Exercises on page 174
b. Complete the Additional Exercises on page 209
INSTRUCTIONS
As doctoral students, your assignments are expected to follow the principles of high-quality scientific standards and promote knowledge and understanding in the field of criminal justice. You should apply a rigorous and critical assessment of a body of theory and empirical research, articulating what is known about the phenomenon and ways to advance research about the topic under review. Research syntheses should identify significant variables, a systematic and reproducible search strategy, and a clear framework for studies included in the larger analysis.
Manuscripts may be written in first person (“I”).
All manuscripts should be clearly and concisely written, with technical material set off. Please do not use jargon, slang, idioms, colloquialisms, or bureaucratese. Use acronyms sparingly and spell them out the first time you use them. Please do not construct acronyms from phrases you repeat frequently in the text.
Structure of Assignment Paper
1. Use the following structure for your research article: Introduction, Methods, Results, Discussion, and Conclusion. Include a robust discussion section distinct from your conclusion.
2. Give your article a Title that is both descriptive and inviting to prospective readers. Your article title should appeal to both scholars and practitioners. Use a shortened version of the main idea of your article in the title.
3. Methods: The Methods section “describes in detail how the study was conducted, including conceptual and operational definitions of the variables used in the study. Different types of studies will rely on different methodologies; however, a complete description of the methods used enables the reader to evaluate the appropriateness of your methods and the reliability and the validity of your results” (APA Style Guide 6th ed., p. 29-32). Include a description of your sample size and procedure, participants, how data collected, and research design.
4. Results include data analysis used, results of the analysis including tables and figures.
5. Discussion section includes interpretations from the analysis. How do your analyses relate to the results found by scholars in your lit review/theory section. In this section, evaluate and interpret their implications, especially with respect to your original hypotheses.
6. Provide a distinct Conclusion that tells readers what you found, why it is important, and what difference it will make for research and practice. Ensure you separate your discussion section from the conclusion of the article. Synthesize your article; do not summarize it. Show readers how the pieces of your article fit together. Answer the question “So what?” Why is your article significant, and how is it relevant?
Note: Your assignment will be checked for originality via the Turnitin plagiarism tool.
Book: SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS 7th ed. Edition
ISBN: 13: 9780335249497
Factors Affecting Individual's Daytime Sleepiness Level
Student's Name
Institutional Affiliation
Course Code and Title
Professor's Name
Date
Introduction
Sleep has several health benefits to the body since it leads to body and brain rest. This results in optimal body performance. In business or social contexts, insufficient sleep hinders the delivery of services and interactions, which are crucial for the success of business or social deals. These are the collective effects of sleep problems like insomnia. These conditions cause one not to get enough restful sleep at night, thus leading to daytime sleepiness. Insufficient sleep, however, negatively impacts a person's mood, judgement, motor skills and reduced energy. This leads to mood swings, anxiety, and fatigue, making a person easily irritated.
Literature Review
Several studies have explored the impact of daytime sleepiness on a person's performance. Ahn et al. (2021) explored individual and occupational factors associated with various levels of daytime sleepiness, identifying their relationship with driving risks among professional workers working for construction firms. They found that most drivers experienced daytime sleepiness and emphasized the significance of reducing the effects of daytime sleepiness, including accidents. Vilela et al. (2016) explored excessive sleepiness frequency and factors associated with it in adolescents. The study found that adolescents experience high rates of sleep deficit, especially students from private schools. Additionally, the study found that sleep deprivation is prevalent in older adolescents and may cause sleeping disorders like sleep hyperhidrosis. In another study, Jaussent et al. (2017) found that common lifestyle and psychological factors predicted sleepiness, which fluctuated over time. Additionally, the study found that prolonged and persistent insufficient sleep was associated with chronic medical conditions.
Methods
The study used a sample size of 271 participants, 35% males and 55% females. Ranging from 18 to 84 years, the average age of the participants was noted as 44 years. The dataset used in this study was the sleep.sav, collected using a questionnaire from university staff in Melbourne, Australia. Participants were provided with a questionnaire about their sleep behavior, sleep problems and their effects on daily life aspects like work, driving and relationships. The study used a correlational design that does not control or manipulate any variables.
Variables
The following variables were used in this research: age, sex, scores on the HADS Depression scale and physical fitness rating and totSAS. Age ranges from 18 to 84 years. Sex is coded 0 to represent female and 1 to indicate male. HADS Depression indicates the total score of the HADS depression scale, ranging from 0 (no depression) to 21 (severe depression). Physical fitness rating ranges from one (very poor) to ten(very good).
TotSAS represents the total score brought about by adding scores of five items (lethargy, tired, fatigue, energy and sleepy) rated on a scale of 1 to 10 in the Sleepiness and Associated Sensations scale. The totSAS has a minimum score of 5, indicating low sleepiness and a maximum of 50, indicating extreme sleepiness.
Results
Standard Multiple Regression
A standard multiple regression was carried out to investigate the factors that affect an individual's daytime sleepiness level. The dependent variable used was the total score of the Sleepiness and Associated Sensations Scale, while the independent variables were age, sex, scores on the HADS Depression scale and physical fitness rating.
Research Questions
1 How much of the variance in total sleepiness scores is explained by the set of variables?
2 Which of the variables make a unique significant contribution?
Table SEQ Table \* ARABIC 1
Descriptive Statistics
Mean
Std. Deviation
N
sleepy & assoc sensations scale
26.04
10.520
251
sex
.45
.498
271
age
43.87
12.684
248
physical fitness
6.42
1.717
266
HADS Depression
3.50
2.993
269
Table SEQ Table \* ARABIC 2
Correlations Table
sleepy & assoc sensations scale
sex
age
physical fitness
HADS Depression
Pearson Correlation
sleepy & assoc sensations scale
1.000
-.199
-.141
-.267
.482
sex
-.199
1.000
-.017
.110
-.071
age
-.141
-.017
1.000
-.039
-.004
physical fitness
-.267
.110
-.039
1.000
-.314
HADS Depression
.482
-.071
-.004
-.314
1.000
Sig. (1-tailed)
sleepy & assoc sensations scale
.
.001
.017
.000
.000
sex
.001
.
.393
.037
.124
age
.017
.393
.
.271
.473
physical fitness
.000
.037
.271
.
.000
HADS Depression
.000
.124
.473
.000
.
N
sleepy & assoc sensations scale
251
251
230
247
249
sex
251
271
248
266
269
age
230
248
248
243
246
physical fitness
247
266
243
266
265
HADS Depression
249
269
246
265
269
Table SEQ Table \* ARABIC 3
Model Summary: Standard Multiple Regression
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.541a
.293
.280
8.927
a. Predictors: (Constant), HADS Depression, age, sex, physical fitness
b. Dependent Variable: sleepy & assoc sensations scale
Table 3 above shows that 29.3% of the variance in total sleepiness scores is explained by the independent variables(age, sex, scores on the HADS Depression scale and physical fitness rating).
Table SEQ Table \* ARABIC 4
Anova Table
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
7413.343
4
1853.336
23.258
.000b
Residual
17929.187
225
79.685
Total
25342.530
229
a. Dependent Variable: sleepy & assoc sensations scale
b. Predictors: (Constant), HADS Depression, age, sex, physical fitness
Table SEQ Table \* ARABIC 5
Coefficients Table
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
95.0% Confidence Interval for B
Correlations
Collinearity Statistics
B
Std. Error
Beta
Lower Bound
Upper Bound
Zero-order
Partial
Part
Tolerance
VIF
1
(Constant)
32.211
3.481
9.255
.000
25.352
39.069
sex
-3.323
1.193
-.157
-2.786
.006
-5.673
-.973
-.199
-.183
-.156
.986
1.014
age
-.121
.047
-.146
-2.604
.010
-.213
-.029
-.141
-.171
-.146
.998
1.002
physical fitness
-.731
.364
-.119
-2.008
.046
-1.447
-.014
-.267
-.133
-.113
.892
1.121
HADS Depression
1.522
.208
.433
7.329
.000
1.113
1.932
.482
.439
.411
.900
1.111
a. Dependent Variable: sleepy & assoc sensations scale
From the Coefficients table, the variable that makes a uniquely significant contribution is the HADS depression since it has the highest standardized beta coefficient (.433). This implies that an increase of HADS depression by one standard deviation increases the total sleepiness score by .433 standard deviations.
Hierarchical Multiple Regression
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Change Statistics
R Square Change
F Change
df1
df2
Sig. F Change
1
.245a
.060
.052
10.243
.060
7.267
2
227
.001
2
.541b
.293
.280
8.927
.232
36.948
2
225
.000
a. Predictors: (Constant), age, sex
b. Predictors: (Constant), age, sex, HADS Depression, physical fitness
c. Dependent Variable: sleepy & assoc sensations scale
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1524.909
2
762.455
7.267
.001b
Residual
23817.621
227
104.923
Total
25342.530
229
2
Regression
7413.343
4
1853.336
23.258
.000c
Residual
17929.187
225
79.685
Total
25342.530
2...
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