When analyzing quantitative research, it’s important to take into account the various steps involved in critiquing the study. You should focus on whether or not the study was conducted properly, how well its findings were interpreted and applied, and whether or not any biases were introduced during data collection. In this article, we’ll explain how to critique quantitative research so that you can evaluate important aspects of studies such as their validity and reliability.
Writing introduction of your critique:
The introduction to your critique should be a short summary of the paper. It is important to include the context of the research, its significance and importance, as well as any limitations. For example:
“This is an excellent paper that provides an in-depth analysis of a specific topic within quantitative research. The authors used sound methods to conduct their study and their results are meaningful in understanding how one can improve upon current practices.”
Identifying the Research Problem.
The first step in critiquing quantitative research is to identify the research problem. This should be fairly straightforward, as you know what your instructor has told you is important to address, and it will be written at the beginning of your assignment. If not, that’s okay too! You can just look at all of your notes from class and see if there are any questions that were asked that you want answered more thoroughly or in more detail than before.
One example of a question that might be asked: “How does gender affect how much time people spend on their homework?” In this case, we would ask ourselves what variables affected how much time people spent on their homework (gender), whether these variables were independent or dependent on one another (how much time spent on homework depends on gender), and whether these variables had any causal effect (does gender cause students to spend less time on homework?).
Defining the Purpose of the Study.
The purpose of the study is to answer a research question, such as “What is the effect of time management training on productivity?” The research question should be clear and specific. In this example, defining what “productivity” means is essential. Also important in this example are choosing whether or not you want to study both individual and organizational effects (or just one), and whether or not success will be measured using a single measure or multiple measures (e.g., employee surveys about their experience with the training).
Questions for consideration:
- Is my research question answerable by my study design? If there are too many variables involved, then it may not be possible to conduct an experiment or quasi-experiment where all but one variable is held constant across subjects. You don’t want your project to fail because you didn’t have enough control over certain factors that could have impacted results!
- On the other hand, if your topic doesn’t lend itself very well towards being studied empirically (e.g., personality traits), then maybe some other type of research method would work better instead; for example, qualitative methods like case studies or ethnographies might work better for trying to understand why people behave as they do rather than simply describing how many hours per day they spend working on projects.
- Examining the Appropriateness of the Design and Methods to Address the Research Question or Hypothesis.
While critiquing quantitative research you should examine the appropriateness of the design and methods to address the research question or hypothesis. You will want to make sure that:
- The study design (e.g., experimental, quasi-experimental, correlational) is appropriate for answering your research question or testing your hypothesis. The selection of study designs is usually done at the proposal submission stage. If you are not sure which design to select, then get dissertation proposal help from experts.
- The sampling method (e.g., population, convenience) is appropriate for understanding the larger group you are studying.
- The research questions are specific enough to be answered in a reasonable timeframe by survey methods (not more than 1 hour), interviews (not more than 3 hours), observation protocols (not more than 2 hours), etc., while still being general enough so they can be applied across different populations and settings without losing consistency or applicability in interpretation results; if not applicable then move on without critiquing this point further as it would waste valuable time when there are many other things left such as sample size, etc.
Assessing Validity, Reliability, and Bias in Research.
Before you can critique the validity, reliability and bias in quantitative research, you need to understand what they are.
Validity is the extent to which a study is able to measure what it claims to measure. The validity of any research depends on several factors including:
- The way that researchers operationalize their variables; for example, if someone was studying intelligence by asking people about their general level of competence and intelligence, this would be an unreliable measure because people may have interpreted the question differently (e.g., some people might consider themselves more intelligent than others)
- Whether or not the sample population accurately represents the target population being studied (e.g., a researcher might have conducted a survey among college students when they were interested in finding out about all ages)
Reliability refers to how consistent results are across studies conducted by different researchers using similar methods/protocols/procedures etcetera over time (i.e., whether or not there’s any “between-study variance” between researchers who use similar methods). A good example of this would be comparing results from different drug trials conducted by pharmaceutical companies.
Determining Significance of Study Findings.
Another important step in critiquing quantitative research is determining significance of study findings. This involves asking yourself, “So what?” and “How does this apply to me?” For example, if you were reading a study about how college students use Facebook and Twitter, then it would be important to ask yourself why you should care about these results. In doing so, you’ll likely find that most studies are only relevant to researchers and those directly affected by their work (i.e., people who are conducting similar studies or using the same methods).
Analyzing Data and Calculating Statistics.
After you’ve read the study, it’s important to analyze the data and calculate statistics. While critiquing quantitative research you should be able to answer these questions:
- How was the data gathered?
- How was the data analyzed?
- How was the data presented?
- How was this information interpreted by the authors of this study?
It’s important to understand the steps involved in critiquing quantitative research in order to become a better scientist and health care provider. By learning about these steps, you can use them to improve your own research and get more out of the work that others have done before you.