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Types of Reliability and Validity
Two metrics are typically used to evaluate reliability: one examines the stability of scale
scores over time, and the other assesses the internal consistency or homogeneity of the items that
make up a scale score. On the other hand, Cronbach's Alpha was calculated using the entire
standardized sample, as indicated by the information obtained in the Values and Motives
Questionnaire (VMQ). The most often used indicator of internal consistency is Cronbach's
Alpha. Only the consistent measurement of an item is ensured by a test with strong internal
consistency and stability coefficients.
Examining a test's validity helps answer questions about what it measures and how
relevant it is in each scenario. Criteria validity and construct validity are two important domains
of validity. This test makes use of construct validity. According to Clark and Watson (2019), The
degree to which theory and data support how test results are interpreted for suggested
applications is known as validity. Thus, while creating and assessing tests, validity is the most
important factor to consider. Therefore, conducting empirical testing of postulated relationships
between theory-based constructs and their observable manifestations is a necessary step in
determining the construct validity of a measure. It was demonstrated through construct validity
that the VMQ is compatible with other assessments that measure the same values and motives as
those investigated in this examination (Values and Motives Questionnaire, nd).
Reliability: Cronbach Alpha Coefficients.
Interpretation
of reliability
coefficient
Excellent
.90 and up
Good
.80-.89
Adequate
.70-.79
Limited
Applicability
Below .70
Affiliative .74
Altruistic .74
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Affection .79
Achievement .53
Finance .83
Security .79
Aesthetics .83
Moral .68
Traditional .70
Independence .66
Ethical .70
S.D. .64
Infrequency .52
Cronbach's Alpha internal consistency reliabilities were computed for the combined male
and female populations. According to What Makes a Test Good (n.d.), eight out of eleven VMI
scales have a score greater than 0.7, which is considered adequate. There were additional
categories with lower numbers on the scale, such as Achievement (.53) and Infrequency (.52).
This VMQ-reported data indicates that five of the scales are below average (.52 to .68), which
puts the dependability virtually at an unsatisfactory level. Moreover, every VMI scale had a
standard error of measurement (SEM) of 0.82 or above, signifying a narrow margin of error. The
more exact the measurement, the smaller the SEM, according to What Makes a Good Test (n.d.).
Sample Size and Nature of Population
Validity
There are many parallels and distinctions between VMI, MAPP, 16PF, and OPP when
comparing their correlations. All the population was a college graduate, although at varying
degrees. The MAPP had 59 undergraduate psychology students agreed to take the test in
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exchange for comments on their scores. The Values and Motivation Questionnaire (n.d.) found
that there were several psychologically significant connections between the VMI and MAPP,
particularly in the value domains that both instruments cover. The remaining 100 MBA students
at a London business school performed the VMI and 16PF version 5 as part of an introduction to
people evaluation techniques. The findings showed that even though the tests are assessing
various aspects of the individual, they are often psychologically significant. The OPP and VMI,
had 59 participants which were given reliable feedback on their test results, and showed a strong
association (VMQ, n.d.).
The individuals who took the VMI tests were limited to college students pursuing degrees
in psychology and business administration. The fact that every participant in the study is an
educated person raises several significant issues. Cultural factors, including a lower
socioeconomic standing, are not as well-represented in this. While the other demographics did
not provide the gender of the participants, the VMQ did reveal that they utilized both male and
female participants. The discrepancy seen in the populations presents one problem with validity.
VMQ Norming Population
In addition to the lack of demographic data, this population's representation of
psychology and MBA college students is limited by the fact that gender information was
withheld from the other groups. These issues make the VMQ unsuitable for use with the broader
public. It was challenging to identify the characteristics of the overall population since the
population was likewise restricted by the number of participants.
Your Opinions of the VMQ
Overall, it appears that the validity and reliability of the VMQ are sufficient.
Nevertheless, data pertaining to the same demographic was absent. It was observed that the
VMQ stated that both men and women completed the questionnaire, which enhanced the validity
of the findings. However, further details are required regarding the sample population's
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References
Clark, L. A., & Watson, D. (2019). Constructing validity: New developments in creating
objective measuring instruments.FPsychological Assessment,F31(12), 1412–1427.
https://doi.org/10.1037/pas0000626F
Values & Motives Inventory. (n.d.). https://psytech.com/Content/TechnicalManuals/EN/Values
& Motives Inventory.pdfF
What Makes a Good Test. (n.d.).
https://canvas.liberty.edu/courses/628416/files/104339333/download?download_frd=1F
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