Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will perform an article critique on t tests. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another.
To prepare for this Discussion:
Review the Learning Resources and the media programs related to t tests.
Search for and select a quantitative article specific to your discipline and related to t tests. Help with this task may be found in the Course guide and assignment help linked in this week’s Learning Resources. Also, you can use as a guide the Research Design Alignment Table located in this week’s Learning Resources
ASSIGNMENT
Write a 3- to 5-paragraph critique of the article. In your critique, include responses to the following:
Which is the research design used by the authors?
Why did the authors use this t test?
Do you think it’s the most appropriate choice? Why or why not?
Did the authors display the data?
Do the results stand alone? Why or why not?
Did the authors report effect size? If yes, is this meaningful?
Required Readings
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.
Chapter 8, “Testing Hypothesis” (pp. 243-279)
Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.
Chapter 6, “Testing Hypotheses Using Means and Cross-Tabulation” (previously read in Week 5)
Chapter 11, “Editing Output” (previously read in Week 2, 3, and 4)
Walden University Library. (n.d.). Course Guide and Assignment Help for RSCH 8210. Retrieved from http://academicguides.waldenu.edu/rsch8210
For help with this week’s research, see this Course Guide and related weekly assignment resources.
Document: Week 6 t test Scenarios (PDF)
Use these scenarios to complete this week’s Assignment. (see attachments)
must be apa written
Must USE SUBHEADING
TURN IT IN REQUIRED
Student Name: Date:
Research Design Alignment Table | Using an alignment table can assist with ensuring the alignment of your research design.
Research Problem, Purpose, and Framework
Provide one sentence for each. These must align with all rows.
Research Question(s), Method, & Design
List one or more RQs, as needed; select method; identify design. Use a separate form for additional RQs.
Data Collection Tools & Data Sources
List the instrument(s) and people, artifacts, or records that will provide the data for each RQ.
Data Points
List the variables, specific interview questions, scales, etc. that will be used for each RQ.
Data Analysis
Briefly describe the statistical or qualitative analysis that will address each RQ.
Problem:
Purpose:
Framework:
RQ1:
Design:
RQ2:
Design:
RQ3:
Design:
Note. The information in the first column must align with all rows, and each individual RQ row must show alignment across the columns for that row.
Once your Research Design Alignment Table is completed, reflect on your design alignment. Ask yourself:
1. Is there a logical progression from the research problem to the purpose of the study?
2. Does the identified framework ground the investigation into the stated problem?
3. Do the problem, purpose, and framework in the left-hand column align with the RQ(s) (all rows)?
4. Does each RQ address the problem and align with the purpose of the study?
5. Does the information across each individual row match/align with the RQ listed for that row?
· By row, will the variables listed address the RQ?
· By row, will the analysis address the RQ?
· By row, can the analysis be completed with the data points that will be collected?
Student Name:
Date:
Research Design Alignment Table
|
Using a
n alignment table
can assist with ensuring the alignment of your research design
.
Research Problem,
Purpose, and Framework
Provide one sentence for each.
These m
ust align with all rows.
Research Question
(
s
), Method,
& Design
List one or more
RQ
s, as needed;
s
elect method;
i
dentify design.
Use a
separate form for additional RQs.
Data Collection Tools
&
Data
Sources
List the
instrument
(s)
and people,
artifacts,
or
records
that will provide
the data for each RQ
.
Data Points
List the variables, specific
interview
questions, scales
,
etc.
that will be
used for
each RQ.
Data Analysis
Briefly describe the
statistical or qualitative
analysis that will address
each RQ.
Problem:
Purpose:
Framework:
RQ1:
Select Method
Design:
RQ2:
Select Method
Design:
RQ3:
Select Method
Design:
Note.
The information in the first column must align with all rows
,
and each individual RQ row must show alignment across the columns for that row.
Once your Research Design Alignment Table is completed, reflect on your design alignment.
Ask yourself
:
1.
Is
there a logical progression from the research problem to the purpose of the study?
2.
Does the identified framework ground the investigation in
to
the stated problem?
3.
Do the problem, purpose, and framework
in the
left
–
hand
column
align with the RQ(s) (all rows
)?
4.
Does each RQ address the problem and align with the purpose of the study?
5.
Does the information across
each individual row
match/align with the RQ listed for that row?
•
By row, will the variables listed address the RQ?
•
By row, will the analysis
address the RQ?
•
By row, can the analysis be completed with the data points that will be collected?
Student Name: Date:
Research Design Alignment Table | Using an alignment table can assist with ensuring the alignment of your research design.
Research Problem,
Purpose, and Framework
Provide one sentence for each.
These must align with all rows.
Research Question(s), Method,
& Design
List one or more RQs, as needed;
select method; identify design. Use a
separate form for additional RQs.
Data Collection Tools & Data
Sources
List the instrument(s) and people,
artifacts, or records that will provide
the data for each RQ.
Data Points
List the variables, specific
interview questions, scales,
etc. that will be used for
each RQ.
Data Analysis
Briefly describe the
statistical or qualitative
analysis that will address
each RQ.
Problem:
Purpose:
Framework:
RQ1:
Select Method
Design:
RQ2:
Select Method
Design:
RQ3:
Select Method
Design:
Note. The information in the first column must align with all rows, and each individual RQ row must show alignment across the columns for that row.
Once your Research Design Alignment Table is completed, reflect on your design alignment. Ask yourself:
1. Is there a logical progression from the research problem to the purpose of the study?
2. Does the identified framework ground the investigation into the stated problem?
3. Do the problem, purpose, and framework in the left-hand column align with the RQ(s) (all rows)?
4. Does each RQ address the problem and align with the purpose of the study?
5. Does the information across each individual row match/align with the RQ listed for that row?
• By row, will the variables listed address the RQ?
• By row, will the analysis address the RQ?
• By row, can the analysis be completed with the data points that will be collected?
Student 1
The quantitative, research article I selected investigates the relationship between one’s job category and organizational deviance. The research design used by the authors was a descriptive-analytical cross-sectional survey. The sampling method was random using the Cochran sampling formula, and the sampling size was 320 employees across five locations (Jahani, Rostami, Mehdizadeh, Mahmoudjanloo, Nikbakht, & Mahmoudi, 2021). The total in the population of employees was 1928 employees.
The author’s selected to analyze the data using an independent t-test because they divided the employees into two groups, (therapeutic and non-therapeutic). The author’s selected the independent t-test because the dependent variable is continuous and they were comparing two groups. The dependent variable, organizational behavior, was measured using 24 items related to organizational membership and were scaled using a likert scale of 1 very low to 5 very high (Jahani, Rostami, Mehdizadeh, Mahmoudjanloo, Nikbakht, & Mahmoudi, 2021).The authors displayed the data in terms of responses and data analysis using multiple tables and charts.
The results do stand-alone in reference to this specific demographic because the information provided is beneficial to existing knowledge on the topic of organizational deviance in terms of demonstrating that one’s job category has a low effect on one’s organizational behavior, they did not account for other environmental factors such as the culture of the organization and the results may not be generalizable outside of hospital employment in Northern Iran.
The effect size was listed as .5 which means that 50% of the variation of organizational behavior can be attributed to job category (Frankfort-Nachmias, Leon-Guerrero, & Davis, 2020). This indicates a moderate effect size which is interesting because the results were statistically not significant, yet the difference is meaningful.
References:
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications
Jahani, M.A., Rostami, F.H., Mehdizadeh, H., Mahmoudjanloo, S., Nikbakht, H.A., & Mahmoudi, G. (2021). Does the job category affect employments’ organizational citizenship behavior in hospitals? Bangladesh Journal of Medical Science, 20(1), 74-80. http://doi-org.ezp.waldenlibrary.org/10.3329/bjms.v20i1.50349
Student 2
According to Heiberger & Neuwirth, (2009). The one-way ANOVA is used to determine whether there are any significant differences between the means of two or more independent groups. They also note that it is important to realize that the one-way ANOVA is an omnibus test statistic and cannot tell you which specific groups were significantly different from each other; it only tells you that at least two groups were different. In this article, the author intends to compare student success in math courses that are offered in three modules. The modules are online, blended and face to face. Since means of three different groups are being compared, the author opts for the One-way ANOVA.
Yes it is. Mark & Wilson, (2001) suggests that there are three common and appropriate tests of comparing means for a group with more than one sample. They are the two-sample t-test, one-way ANOVA, and two-way ANOVA. A two-sample t-test and two-way ANOVA are the majorly used tests for investigating a significant difference when we have more than one sample. However, the t-test is only applicable when we have two and only two factors or samples. For the two way ANOVA, it compares the mean differences between groups that have been split on two independent variables (called factors). The primary purpose of a two-way ANOVA is to understand if there is an interaction between the two independent variables on the dependent variable.
In this study, the research was interesting and only had three samples that he wanted to compare. This means neither the two-sample t-test nor the two-way ANOVA tests would be appropriate. The one-way ANOVA is best suited for this study and thus we can conclude it was the most appropriate test used in the article. Khan, (2016) argues that data ought to be displayed in a form that is easily comprehensible by a lay reader. In this study, the data was displayed in tables. The first table titled demographics showed the frequencies of each module and the demographics of each which included gender, race, and age. One-way ANOVA tables were then displayed on the data analysis segment to show the findings of the study. These tables were presented in a way that they are clear and exact in detail.
The results in the ANOVA table Standalone. This is because the results were found to be significant. The researcher found out that out of the three study modules, students that took the face to face module scored highest while those who took the online module scored the least. The blended module students scored in between the face-to-face and the online module. The P-value of ANOVA was less than 0.05 and thus it would be concluded that the study was significant. The results can be well utilized in the education sector to help put measures in place for improving content delivery to students using the online and blended modules. Since a large sample size was used and an appropriate test was conducted for the data and all underlying assumptions of a one-way ANOVA were met, the results can be termed as reliable and generalized for the entire population.
References:
Ashby, J., Sadera, W. A., & McNary, S. W. (2011). Comparing student success between developmental math courses offered online, blended, and face-to-face. Journal of Interactive Online Learning, 10(3), 128-140.
Heiberger, R. M., & Neuwirth, E. (2009). One-way anova. In R through excel (pp. 165-191). Springer New York.
Khan, A. (2016). Displaying Underlying Data. In Jumpstart Tableau (pp. 249-254). Apress.
Mark W.. Lipsey, & Wilson, D. B. (2001). Practical meta-analysis (Vol. 49). Thousand Oaks, CA: Sage publications.
Student 3
Write a 3- to 5-paragraph critique of the article. In your critique, include responses to the following:
Article: Trauma Processing Reconsidered: Using Account-Making in Quantitative Research With Male Survivors of Child Sexual Abuse (2013)
By: Scott D. Easton
According to Laureate Education (2016), “the independent t-test is a comparison of means tests that compares two means across an independent categorical variable”.
· Which is the research design used by the authors?
The research design used by the author is that of a Quantitative Research. According to author Easton (2013), the study was meant to show how survivors process loss and trauma by using Account-making. Account-making is “a social psychological model that describes the adjustment process of people who have encountered severe stressor and traumatic event, or significant personal loss” (Easton, 2013).
· Why did the authors use this t test?
The author used this t-test to measure the characteristics of the recovery process related to mental distress. Also, the t-tests were conducted and found support in the fact that participants who met the criteria for denial produced higher scored when it came to mental distress, compared to participants who did not meet said criteria for denial.
· Do you think it’s the most appropriate choice? Why or why not?
Based on the research conducted and the projected outcome within the research, I feel as if it was the most appropriate choice for it validates the findings of researchers based on the two different groups being investigated. It also helps portray the significant difference related to specific features between participants.
· Did the authors display the data?
The Author displayed data of their research through tables that displayed the results for Account-Making stages and Relation to Mental Distress (N = 487).
· Do the results stand alone? Why or why not?
The results stand alone for they are contributing to statistical data and knowledge that already exists. The research within the article provides an additional way to measure the mental distress undergone by those who have been subject to traumatic abuse and/or loss.
· Did the authors report effect size? If yes, is this meaningful?
The author reports effect size was .05 in which the results indicated that there was a negative relationship between the scores gathered through the Account Development Scale and mental distress. Previous research that had been conducted, however, found positive relationships between account development, coping, and adjustment for sexual abuse survivors. I feel this is meaningful for it not only adds to already gathered statistical data, but it also fills any statistical gap when it comes to the aftereffects of abuse with its focus on one particular sex.
Resources
Easton, S.D. (2013). “Trauma Processing Reconsidered: Using Account-Making in Quantitative Research With Male Survivors of Child Sexual Abuse” Retrieved from https://eds-b-ebscohost-com.ezp.waldenulibrary.org/eds/pdfviewer/pdfviewer?vid=8&sid=d8bad288-63b9-4da7-adc8-985bbcee34a3%40pdc-v-sessmgr03
Laureate Education (Producer). (2016). The t test for independent samples [Video file]. Baltimore, MD: Author. Dr. Matt Jones, demonstrated the t Test for independent samples in SPSS.
Student 4
he article, Quantitative and qualitative differences in the lexical knowledge of monolingual and bilingual children on the LITMUS-CLT task written by Altman, Goldstein and Armon-Lotem was chosen as it is categorized in Public Policy and Administration, in a field of personal interest (bilingualism) using a quantitative method.
The authors indicated they used the t-test for independent sampling as a way to conduct comparisons between two groups: monolingual and bilingual children (Altman, Goldstein & Armon-Lotem, 2017). The use of a t-test in this research is appropriate as it aligns with the definition of a t-test, “The independent samples t-test is a comparison of means test that compares two means across an independent categorical variable” (Laureate Education (Producer), 2016l).
The authors compare two groups of children to understand their “comprehension and production of nouns and verbs” how significant the differences are, measured in means (Altman, Goldstein & Armon-Lotem, 2017). They then used a Generalized Linear Model (GLM) to evaluate effects and interactions between the groups (Altman, Goldstein & Armon-Lotem, 2017). One group spoke Hebrew only, and the other Russian and Hebrew (Altman, Goldstein & Armon-Lotem, 2017).
The authors provided eight tables and one figure to express the data collected. The data from this research contributes to current literature on language acquisition. This quantitative research design builds upon current literature and addresses challenges that were found in past literature. It also allows for additional research to build from this research. It appears there was no effect size reported. However, this does not affect the results of the research. The research is meaningful as it can be functional to real world application.
References
Altman, C., Goldstein, T., & Armon-Lotem, S. (2017). Quantitative and qualitative differences in the lexical knowledge of monolingual and bilingual children on the LITMUS-CLT task. Clinical Linguistics & Phonetics, 31(11/12), 931–954. https://doi-org.ezp.waldenulibrary.org/10.1080/02699206.2017.1312533
Laureate Education (Producer). (2016l). The t test for independent samples [Video file]. Baltimore, MD: Author.
Student
1
The
quantitative,
research
article
I
selected
investigates
the
relationship
between
one’s
job
category
and
organizational
deviance.
The
research
design
used
by
the
authors
was
a
descriptive
–
analytical
cross
–
sectional
su
rvey.
The
sampling
method
was
random
using
the
Cochran
sampling
formula,
and
the
sampling
size
was
320
employees
across
five
locations
(Jahani,
Rostami,
Mehdizadeh,
Mahmoudjanloo,
Nikbakht,
&
Mahmoudi,
2021).
The
total
in
the
population
of
employees
was
19
28
employees
.
The
author’s
selected
to
analyze
the
data
using
an
independent
t
–
test
because
they
divided
the
employees
into
two
groups,
(therapeutic
and
non
–
therapeutic).
The
author’s
selected
the
independent
t
–
test
because
the
dependent
varia
ble
is
continuous
and
they
were
comparing
two
groups.
The
dependent
variable,
organizational
behavior,
was
measured
using
24
items
related
to
organizational
membership
and
were
scaled
using
a
likert
scale
of
1
very
low
to
5
very
high
(Jahani,
Rostami,
Mehd
izadeh,
Mahmoudjanloo,
Nikbakht,
&
Mahmoudi,
2021).The
authors
displayed
the
data
in
terms
of
responses
and
data
analysis
usin
g
multiple
tables
and
charts
.
The
results
do
stand
–
alone
in
reference
to
this
specific
demographic
because
the
infor
mation
provided
is
beneficial
to
existing
knowledge
on
the
topic
of
organizational
deviance
in
terms
of
demonstrating
that
one’s
job
category
has
a
low
effect
on
one’s
organizational
behavior,
they
did
not
account
for
other
environmental
factors
such
as
th
e
culture
of
the
organization
and
the
results
may
not
be
generalizable
outside
of
hospital
employment
in
Northern
Iran
.
The
effect
size
was
listed
as
.5
which
means
that
50%
of
the
variation
of
organizational
behavior
can
be
attributed
to
job
categor
y
(
F
rankfort
–
Nachmias,
Leon
–
Guerrero,
&
Davis,
202
0
)
.
This
indicates
a
moderate
effect
size
which
is
interesting
because
the
results
were
statistically
not
significant,
yet
the
difference
is
meaningful
.
References
:
Frankfort
–
Nachmias,
C.,
Leon
–
Guerrero,
A.,
&
Davis,
G.
(2020)
.
Social
statistics
for
a
diverse
society
(
9
t
h
ed.)
.
Thousand
Oaks,
CA:
Sage
Publication
s
Jahani,
M.A.,
Rostami,
F.H.,
Mehdizadeh,
H.,
Mahmoudjanloo,
S.,
Nikbakht,
H.A.,
&
Mahmoudi,
G.
(2021).
Does
the
job
category
affect
employments’
organizational
citizenship
behavior
in
hospitals
?
Bangladesh
Journal
of
Medical
Science,
20
(1),
74
–
80.
http://d
oi
–
org.ezp.waldenlibrary.org/10.3329/bjms.v20i1.5034
9
Student 2
According
to
Heiberger
&
Neuwirth,
(2009).
The
one
–
way
ANOVA
is
used
to
determine
whether
there
are
any
significant
differences
between
the
means
of
two
or
more
independent
groups.
They
also
note
that
it
is
important
to
realize
that
the
one
–
way
ANOVA
is
an
omnibu
s
test
statistic
and
cannot
tell
you
which
specific
groups
were
significantly
different
from
each
other;
it
only
tells
you
that
at
least
two
groups
were
different.
In
this
article,
the
author
in
tends
to
compare
student
success
in
math
courses
that
are
offered
in
three
modules.
The
modules
are
online,
blended
Student 1
The quantitative, research article I selected investigates the relationship between one’s job
category and organizational deviance. The research design used by the authors was a descriptive-
analytical cross-sectional survey. The sampling method was random using the Cochran sampling
formula, and the sampling size was 320 employees across five locations (Jahani, Rostami,
Mehdizadeh, Mahmoudjanloo, Nikbakht, & Mahmoudi, 2021). The total in the population of
employees was 1928 employees.
The author’s selected to analyze the data using an independent t-test because they divided
the employees into two groups, (therapeutic and non-therapeutic). The author’s selected the
independent t-test because the dependent variable is continuous and they were comparing two
groups. The dependent variable, organizational behavior, was measured using 24 items related to
organizational membership and were scaled using a likert scale of 1 very low to 5 very high (Jahani,
Rostami, Mehdizadeh, Mahmoudjanloo, Nikbakht, & Mahmoudi, 2021).The authors displayed the
data in terms of responses and data analysis using multiple tables and charts.
The results do stand-alone in reference to this specific demographic because the information
provided is beneficial to existing knowledge on the topic of organizational deviance in terms of
demonstrating that one’s job category has a low effect on one’s organizational behavior, they did
not account for other environmental factors such as the culture of the organization and the results
may not be generalizable outside of hospital employment in Northern Iran.
The effect size was listed as .5 which means that 50% of the variation of organizational behavior
can be attributed to job category (Frankfort-Nachmias, Leon-Guerrero, & Davis, 2020). This
indicates a moderate effect size which is interesting because the results were statistically not
significant, yet the difference is meaningful.
References:
Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society
(9
th
ed.). Thousand Oaks, CA: Sage Publications
Jahani, M.A., Rostami, F.H., Mehdizadeh, H., Mahmoudjanloo, S., Nikbakht, H.A., & Mahmoudi, G.
(2021). Does the job category affect employments’ organizational citizenship behavior in
hospitals? Bangladesh Journal of Medical Science, 20(1), 74-80. http://doi-
org.ezp.waldenlibrary.org/10.3329/bjms.v20i1.50349
Student 2
According to Heiberger & Neuwirth, (2009). The one-way ANOVA is used to determine
whether there are any significant differences between the means of two or more independent
groups. They also note that it is important to realize that the one-way ANOVA is an omnibus test
statistic and cannot tell you which specific groups were significantly different from each other; it
only tells you that at least two groups were different. In this article, the author intends to compare
student success in math courses that are offered in three modules. The modules are online, blended
