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Logistic Regression and Healthcare Research Design

Quantitative Design

Considering the topic of the perspective investigation as well as its goals, the method of logistic regression may be applied in terms of the quantitative design. Logistic regression is a useful classical tool for resolving the issues of regression and classification, serving as an apparatus for analyzing the quality of models. This is a type of multiple regression, the specific purpose of which is to analyze the relations between several independent variables that are also called regressors or predictors and a dependent variable (Bennett, Briggs, & Triola, 2014). In other words, with the help of logistic regression, one can estimate the probability with which an event will occur for a particular subject.

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The applicability of the suggested method is caused by it is widespread use in medicine and conduct clinical studies and accurate nature. Among the strengths of logistic regression, one may note that it is easy to perform, the opportunity to embrace wide populations, and reliability along with validity (Bennett et al., 2014). It should also be emphasized that this method has the shortcoming that is associated with the inability to make the most reliable estimate. In particular, in the process of modeling, inconsistencies in the output values ​​of the model and the real values ​​of the sample may occur. For example, the prediction corresponding to a positive outcome can be recognized by the model as a negative outcome (false negative error, the error of the first kind), and that corresponding to a negative outcome, on the contrary, can be identified by the model as a positive outcome (false positive error or type II error). Therefore, the model focuses on four potential outcomes.

Qualitative Design

The qualitative design would focus on the survey method that implies the acquisition of deep and detailed information about the subject of the research. It answers such questions as “how?” and “why?”, while using quantitative research methods, one can get an answer to the question “how much?”. The strong aspects of this design include the following points: it allows directly capturing and recording acts of behavior, simultaneously identifying characteristics of some persons about each other or certain tasks, subjects, etc. (Grove, Gray, & Burns, 2015). The survey makes it possible to achieve multidimensional coverage, fixing several parameters at the same time, for example, verbal and non-verbal behavior. The appropriateness of qualitative design to the prospective study is evident as the latter would investigate nursing turnover rates and causes to come up with the relevant recommendations on how to improve the current situation. As the mentioned theme presents various factors related to people, patients, and nursing in general, the survey would reveal the key issues and foster some ways of addressing the existing issue.

However, the multiplicity of irrelevant or disturbing factors acts as weaknesses of qualitative design. The results of the survey can be affected by the prejudice of the observer, the complexity of the situations, errors in estimates, and contrast mistakes (Grove et al., 2015). Moreover, there is the one-time nature of the survey, leading to the inability to make the generalized conclusion based on single observable facts. The need to classify the results of the survey along with the requirement of large resources, including temporary, human, material, and so on also may be considered as weak points. The complexity of adherence to the operational rigor creates some difficulties as well.


Bennett, J. O., Briggs, W. L., & Triola, M. F. (2014). Statistical reasoning for everyday life (4th ed.). Boston, MA: Pearson.

Grove, S. K., Gray, J., & Burns, N. (2015). Understanding nursing research: Building an evidence-based practice (6th ed.). St. Louis, MO: Elsevier.

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