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Writing the Assumptions and Limitations

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Writing the Assumptions and Limitations
What ARE the Assumptions? Assumptions are those things we take for granted in the study: statements by the researcher that certain elements of the research are understood to be true. While assumed, they should still be explicitly stated in the body of the dissertation, usually in chapter 1.
Types of Assumptions Assumptions are made about (a) the theory under investigation, (b) the phenomenon under investigation, (c) the instrument, (d) the methodology, (e) the analysis, (f) the power to find significance, (g) the participants in the study, and (h) the results.
What ARE limitations?

Limitations are those elements over which the researcher has no control. In most instances, any assumption you make becomes a limitation.

Delimitations are those elements the researcher CAN control (see the limitations and delimitations page for more information).

Assumption:
Theoretical Foundation
After writing the theoretical foundation of your study, you, the researcher, are making the assumption that the foundation of your study is sound. The theoretical framework is assumed to be an accurate reflection of the phenomena being studied. Therefore, the results of your study are limited by the accuracy of the theoretical framework to reflect the phenomena under study.
Limitation:
Theoretical Foundation
Consider the variables self-esteem (belief in yourself) and self-efficacy (belief in your abilities). If the theoretical foundation of your study was based on one of these variables, and the variable you actually measured was the other, then the theoretical foundation of your study may be flawed. This limits the accuracy of your results. So a study is limited by whether the theoretical foundation of your study is an accurate reflection of the phenomena/variables you are studying.
Assumption:
The Phenomenon

Before beginning your study, the phenomenon under investigation must be clearly defined, and it must be measurable. It is assumed the variables have been clearly defined and are measurable. For qualitative studies, you assume that the participants are aware of and able (and willing) to discuss the phenomenon under investigation to help you draw conclusions to address the purpose of the study.

Limitation:
The Phenomenon
Many theoretical constructs measured in the social sciences are difficult to define. Review studies on concepts such as job satisfaction or student success, and you will find different definitions and different measurement instruments. Your study is limited by your definition (how broadly or narrowly you define the phenomenon under investigation). For example, one might measure student success by test scores, graduation rates, or employment after completion. The results of your study will vary widely, depending on which of these definitions you select!
Assumption:
The Instrument

The researcher assumes that the variables under investigation are measurable (sounds easy: gender, age, etc., but how do you measure happiness?), and the instrument being used is a valid and reliable instrument to measure those variables. For qualitative studies, you assume that the interview questions accurately reflect the phenomenon and will allow you to elicit rich textural data to address the research question. You also assume that any documents you collect will contain the information necessary to draw valid and reliable conclusions. If you are conducting observations, you assume that you or other observers will be unbiased in reporting what was observed. 

Limitation:
The Instrument
Instruments are limited by their reliability and validity. An instrument is reliable if it will give the same measurement every time when measuring the same construct. Consider weight - if you weigh yourself at home, then weigh yourself 5 minutes later, you should get the same measurement unless YOU have changed (put on/removed clothes). That's reliability. If you weigh yourself at home, you may get a different measurement than at the doctor's office or the gym. Which scale is valid? If the density of the ground below each area is different, they ALL may be valid. If the density is the same, you need to determine WHICH scale is giving you the correct weight - only ONE is valid.
Assumption:
The Methodology
The researcher assumes the methodology is appropriate to the problem being addressed and the purpose of the study. For example, quantitative analysis is rarely appropriate to address how or why questions.
Limitation:
The Methodology
The results of the study are limited by the ability of the methodology to address the problem and purpose. You might address the same research questions by several different methodologies. WHICH methodology you choose may increase or decrease your ability to find the answer you are seeking.
Assumption:
The Analysis

Every statistical procedure has certain requirements. For example, most parametric analyses (e.g., Pearson correlations, ANOVAS) require normally distributed data. Therefore, you, as the researcher, assume that the data will be normally distributed. If the data are NOT normally distributed, then you might consider using a nonparametric procedure such as Spearman Rho instead of the Pearson correlation coefficient.

Limitation:
The Analysis
The results of your study are limited by the ability of the statistical procedure selected to find statistical significance. The analysis must be appropriate to address the research question, and the test must have sufficient power to detect significance differences/relationships if they exist in the population.

Assumption:
The Power to Detect

Before conducting the analysis, the researcher assumes that the analysis selected and the size of the sample are sufficient to detect significant differences/relationships if they exist in the population.
Limitation:
The Power to Detect
The results of your study are limited by the ability of the statistical test to detect significant differences/relationships if they exist in the population (note: you will likely *not* find differences in your sample if they DO NOT EXIST in the population!).
G*Power is a free software program designed to determine the power of statistical tests.
Assumption:
The Participants
In order for a study to be valid, the participants must be representative of the population, must be willing to participate in the study, and must respond to questions honestly or participate without biasing the study results (i.e., not behaving differently than they would were they not participating in a research study).  In a qualitative study, the participants must have sufficient knowledge to provide information necessary to answer the research question, and they must be willing to share, and be honest in sharing. .
Limitation:
The Participants
Your study is limited by how well the participants in the study represent the population (this is why sample selection is so important! Nonrandom sampling means your participants likely do not represent the population). In addition, the results of your study are limited by the honesty of your participants, or their nonbiased participation (i.e., not changing their behavior because they know they are participating in a study).
Assumption:
The Results
Once your analysis is complete, you assume that the results are generalizable beyond the sample being studied. Finally, it is assumed that the results of the study will be relevant to stakeholders. This is the most compelling assumption: that the results will be meaningful.
Limitation:
The Results
The generalizability is limited by how well the sample represents the population. The study is also limited by the usefulness of the results to important stakeholders.

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Diane M. Dusick, Ph.D.
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