Writing the Limitations and Delimitations
|What ARE limitations?||Limitations are those elements the researcher has no control over. In most instances, any assumption you make (see the ASSUMPTIONS page) becomes a limitation|
|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.
|Limitations based on assumptions: 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.|
|Theoretical Foundation: Example||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|
|Limitations based on assumptions: 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.
|The Phenomenon: Example||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!|
|Limitations based on assumptions: 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.|
|The Instrument: Example||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.|
|Limitations based on assumptions: 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.|
|The Methodology: Example||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.|
|Limitations based on assumptions: 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.
|The Analysis: Example||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.|
|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. G*Power is a free software program designed to determine the power of statistical tests.|
|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).|
|The Results||Once your analysis is complete, you assume that the results are generalizable beyond the sample being studied. The generalizability is limited by how well the sample represents the population. 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.|
|What ARE Delimitations||Delimitations are those things the researcher CAN control.|
The researcher has complete control over participant selection. Start by clearly defining your population: the population consists of all people (or things) belonging to the group from which you will select your participants (or subjects for an experimental or quasiexperimental design). In this case, clearly describe all unique variables that define your population.
This may include only women, or only students enrolled in a college full time, or anyone 21-35 years old, or nurses who have worked in an acute care setting for at least 5 years.
|Geographic location||We often delimit studies to a specific geographic location - clearly describe the boundaries: the state of California, or all community colleges in California from Bakersfield to San Diego, or all private hospitals with over 300 beds in the city of Chicago.|
|Time Constraints||You may delimit your study to a specific time period, so only students enrolled in school during fall, 2014.|
|Other Delimiting Variables||Remember, delimitations are those elements, you, the researcher can control. So examine all the variables or factors in your study. How will you choose to include or exclude any participant? Anyone who is excluded because they do not meet a certain qualification is a delimitation.|
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Diane M. Dusick, Ph.D.
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