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Logistic Regression Used in Three Healthcare Articles

Review of the articles

The article “Impact of individual-, environmental-, and policy-level factors on health care utilization among US farm workers” discusses the results of a study on the number of US farmworkers who can access US health care. The study considered this question on the levels of individual, environmental, and policy. The study used logistic regression to analyze the multivariate data gathered.

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The other article, “Prediction of influenza vaccination outcome by neural networks and logistic regression,” describes the methods and results of a neural network study on the effectiveness of the influenza vaccine using historical data in three neural network algorithms (Tritica-Majnaric et al. 2010). The article also provides a discussion of logistic regression in comparison to the neural network algorithms used.

Finally, the article “Nearest-neighbor and logistic regression analyses of clinical and heart rate characteristics in the early diagnosis of neonatal sepsis” outlines the procedures and findings of a study through the use of two methods of neonatal sepsis diagnosis: nearest-neighbor analysis and logistic regression analysis (Xiao et al. 2010). The results indicated that each method generated unique information useful for diagnosis, and therefore both methods should be used simultaneously for improved accuracy of diagnosis.

Critical review of the articles

Goals and purposes of the research case study

The article, “Impact of individual-, environmental-, and policy-level factors on health care utilization among US farm workers,” discusses the results of a study of the number of US farmworkers who can access US health care. The study considered this question on the levels of individual, environmental, and policy. The study used logistic regression to analyze the multivariate data gathered.

Logistic regression in the research study

With a sample of 2884 respondents, the environmental variables that were derived are geographic information, border indices, and uniform data system. The variables were modeled on a standard weighted hierarchal linear model. The individual level provided the baseline for independent evaluation, while the policy level facilitated dependent evaluation (Hoerster et al., 2011). Through logistic regression, the findings indicated that the sample design conformed to the null hypothesis that farmworkers had limited access to health services in the US. However, the level of risk was dependent on the individual level of each research subject.

Alternative quantitative and statistical methods

The other alternative can be the use of simple correlation analysis involving the measurement of dependent and independent variables. These variables will be geographic information, border indices, and uniform data system. The simultaneous application and measurement of independent and dependent variables capture the true value representation of the target population. In addition, the authors can use intrusive regression analysis that quantifies the relationship between two variables. The relationship between the two variables can be expanded to more variables grouped in pairs.

Strengths and weaknesses of the study

When properly used, regression analysis produces quantifiable and realistic results within a minimal error range. This method can be repeated for different measurement variables to obtain an accurate relationship and correlation between every pair of quantifiable factors. Due to the special nature of the interest group, the study has not captured an accurate picture since each geographic information, border indices, and uniform data system are not universal.

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Reversing the weaknesses of the study

In order to quantify the relationship between the independent and dependent variables, ANOVA analysis should be done to lower the degree of error. Once respective values are obtained, it is easier to mathematically draw intrinsic and extrinsic relationships between dependent and independent variables.

Contributions of the findings to evidence-based practice

The essential part of a properly written research paper should reflect on conceptualization and maintain originality. This research paper provides a clear link between one variable to another and is majorly based on verifiable conclusions. Besides, the analysis presents a complete reflection of the actual situation in different research groups. Thus, a nurse or nursing body may use this study in policy development and the creation of a practical response mechanism to the challenges mentioned.

References

Hoerster, K. D., Mayer, J. A., Gabbard, S., Kronick, R. G., Roesch, S. C., Malcarne, V. L., & Zuniga, M. L. (2011). Impact of individual-, environmental-, and policy-level factors on health care utilization among US farm workers. American Journal of Public Health, 101 (4), 685–692.

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., & Vitale, B. (2010). Prediction of influenza vaccination outcome by neural networks and logistic regression. Journal of Biomedical Informatics, 43 (5), 774–781.

Xiao, Y., Griffin, M. P., Lake, D. E., & Moorman, J. R. (2010). Nearest-neighbor and logistic regression analyses of clinical and heart rate characteristics in the early diagnosis of neonatal sepsis. Medical Decision Making, 30 (2), 258–266.

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