How does a research problem/question guide the determination to conduct a quantitative versus a qualitative research study?
The research question directly correlates with the type of relationship under investigation. Quantitative and qualitative studies differ in their approach to examining relationships (Polt & Beck, 2017). Therefore, selecting a quantitative study for research questions that focus on causal relationships may be better just as a qualitative study would apply to associative relationships.
Discuss the value of using a conceptual framework or theory (grand or mid-range) to guide a quantitative research study. Address the debate of the appropriateness of using of a conceptual framework or theory to guide a qualitative research study
Quantitative research commonly attempts to test hypotheses that have been deduced from existing or proposed theory, linking the experiment to the conceptual framework. It is valuable because theoretical models can be used as an organizing structure or interpretive tool. Although qualitative research is commonly based upon or includes a theoretical framework, there is a debate to its appropriate use in research. This is due to a lack of consistency and proper utilization of conceptual models. While some researchers take the steps of “holding in check all prior knowledge,” others, such as ethnographic studies actively utilize socio-cultural theories (Polt & Beck, 2017). It is suggested that a smart approach is taken towards theory utilization by implementing boundaries of the concept of interest.
What specific types of research designs are used in quantitative research? What specific types of designs are used in qualitative research?
The experimental design influences the decision of selecting quantitative or qualitative research. For example, experimental research or nonexperimental data collection is more conducive for quantitative studies. Meanwhile, grounded theory, and phenomenologic or ethnographic research is fitting with a qualitative approach.
What are differences in determining sample size between quantitative and qualitative research studies?
It is important for a study to determine an optimal sample size that would fit its parameters while remaining within the appropriate available boundaries for time and funding. Quantitative research, which uses regression analysis for its data analysis, requires an adequate sample size to avoid type II errors and misleading regression coefficients. Some methods include using the ratio of predictor variables or a power analysis to estimate a sample size necessary to reject the null hypothesis. Qualitative researchers make sampling decisions during the course of the study and rarely have a predetermined sampling plan (Polt & Beck, 2017).
Discuss the difference in methods of data analysis for quantitative research versus qualitative research studies
Qualitative data analysis is challenging as there are no universal standards or procedures. It consists of compiling and transcribing significant amounts of qualitative data in forms of interviews or observations. Commonly, a coding scheme is developed to organize and cluster the data to ensure its validity and presentability. Data coding and management occurs that derives themes and short segments from large texts.
Meanwhile, quantitative data analysis is extensive and complex, depending on the amount of data and software or methods chosen by researchers. Although, there are standard analyses that are commonly performed on certain types of data. The data is first input into software programs and coded. Issues such as missing values are addressed, and data is evaluated for quality and value. The principal analyses consist of descriptive, bivariate inferential, multivariate, and regression statistical tests (Polt & Beck, 2017).
Discuss methods of insuring scientific rigor in quantitative research studies versus qualitative research studies
Enhancing scientific rigor, particularly in qualitative studies, means enhancing the quality and credibility of the research. Some methods in qualitative research include enhancement of data collection by using prolonged engagement and persistent observation. Delimiting subjectivity and maintaining reflexivity are encouraged as well. Data coding should undergo transcription rigor, triangulation, intercoder checks, peer review, and inquiry audit, with all steps reflecting in-depth description and transparency during the presentation of findings. Qualitative studies follow criteria of models by Guba & Lincoln or Whittemore et al (Polt & Beck, 2017).
Quantitative studies ensure rigor by attempting to minimize bias and control confounding variables. Some techniques include randomization of its sample groups, using a crossover, and potentially introducing homogeneity. Statistical control mechanisms such as analysis of covariance are helpful in controlling of confounding variables. Conclusional validity can be supported by restriction of range, low statistical power, and manipulation checks to interventions.
Discuss the difference in generalizability of quantitative versus qualitative research
External validity, in the form of sampling, often affects generalizability for both types of research. The qualitative research attempts to provide a contextual understanding of humans; therefore, generalizability is rarely the issue as the research design already considers this aspect. Qualitative studies should consider a balance of generalizability and extrapolation from a sample. The quantitative research views generalizability a key quality criterion. Common methods used are statistical and analytic generalization with some discussion of transferability and clinical significance (Polt & Beck, 2017).
Reference
Polit, D. F., & Beck, C. T. (2017). Nursing research: Generating and assessing evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluewer.