Running head: SOURCES OF MEASUREMENT ERROR
Assignment 4.4:
Sources of Measurement Error
Jessica Phung
Bellevue University
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SOURCES OF MEASUREMENT ERROR
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Abstract
The purpose of this paper is to discuss the four major sources of measurement error. The first source I
will discuss is the respondent. Next, I will explain the situational factor. Then, I will explore the
interviewer or measurer in a study. Finally, the last source of distortion I will discuss is the instrument
itself. I will provide an example after the discussion of each source of measurement error.
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Ideally, studies should be designed and controlled to produce the most efficient measurements of
variables. However, since complete control is not possible there's room for error. There are four main
sources that produce measurement error: the respondent, the situation, the measurer, and the data
collection instrument.
The first source of error is the respondents or the participants in the study. The proposed error for
the respondent comes in the form of differing opinions that can affect measurement. The opinions maybe
about employee status, ethnic group membership, social class, et cetera. The researcher is usually
accustomed to this typical issue and will often redesign aspects of the study to accommodate and or fix
these issues, however the researcher may miss a certain dimension. In some cases, the respondent may be
reluctant to express negative connotations or may not want to admit their ignorant about a certain topic.
All this can result in useless data because the information may have been falsified or assumed.
Participants can also suffer from temporary behavioral issues such as anxiety, fatigue, boredom, etc.
which affects their ability to respond accurately and purposefully. An example of measurement error that
involves the respondent is when our customers fill out a departmental feedback survey. Customers rate us
on their personal experiences, as our business processes are the same for all of our customers. One
customer gave a bad reading simply because they lack the authority to perform and complete the project
on their own, even though the project performance rating was flawless. This one customer is an example
of how the respondent’s opinion can affect the rest of the data just based upon opinion alone.
The second source of error lies in the situational details. "Any condition that places a strain on the
interview or measurement session can have serious effects on the interviewer – respondent rapport"
(Cooper & Schindler, 2011). Any additional person other than the respondent can be a distraction as the
extra party can influence responses or interject haphazardly. Demonstration of a measurement error due
to a situational factor is evident within my organization when our customers leave third-party survey
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responses. In other words, the customers who requested our services are not the end-users leaving the
survey responses. This causes an issue with an accurate responses because a third-party leaving the
feedback was not that end-user receiving the requested service.
The third source of error is the interviewer or the measurer in the study. The interviewer can
warp the responses through the "rewording, paraphrasing, or reordering questions" (Cooper & Schindler,
2011). Bias can be introduced through stereotype appearances and actions, conscious or unconscious
prompts like smiles, nods, etc. that may encourage and/or discourage the respondents replies. Further
errors can also be introduced through "Incorrect coding, careless tabulation, and faulty statistical
calculations" (Cooper & Schindler, 2011). An example of the measurer being the cause of an erroneous
measurement is demonstrated through the use of a metrics manager within my organization. Our metrics
manager manually compiles the data into spreadsheets and charts that are senior management request at
our weekly production meetings. Every once in a while, our metrics manager will accidentally input data
into the wrong field. This results in the calculations of our performance reports to be slightly off because
the data was input correctly.
The fourth source of error distortion is found in the instrument itself and can cause issues in
two ways. The first way is that the instrument is just complex and confusing; everything from the
terminology, to multiple questions, to mechanical defects can attribute to aid direct result of improper
planning. The second way, involves a poor selection of items included in the study. The instrument being
the source of measurement here within my organization can be demonstrated by the use of our customer’s
feedback surveys. Our surveys ask our customers the following questions: how satisfied were you with
your service request? And rating from 1 to 10, how likely are you to recommend our services to another
person? Our instrument design may be flawed, as our data selection is limited because no further
questions are asked.
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References
Cooper, D.R., & Schindler, P.S. (2011). Business research methods. New York, NY:McGraw Hill Irwin.