Measurement Level in Nursing Practice - Special Academic Support

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Introduction

Nursing research involves exploration of best practices, which are aimed at improving service delivery. To achieve best practices, nursing incorporates research on evidence-based practice. Additionally, nursing research explores new areas to find possible inputs in care giving. Consequently, nursing practice is part of research. Moreover, research involves analysis of data with the aim of establishing links between conceptual framework and nursing. To provide acceptable analysis, statistical techniques such as SPSS, among others are usually utilized. This paper will explore levels of measurements in SPSS (Polit, 2010).

Research question

Research questions are usually essential for nursing research because they probe the topics of interest. Additionally, research questions inquire about information required for completion of nursing research. For this assignment, the research question would be as follows:

What is the significance of using level of measurements in statistical analysis?

Independent and dependent variables

Nursing research utilizes statistical synonyms in research. These include independent and dependent variables. A variable can be defined as something one is trying to measure. A variable can be an object or event, among others. Independent variables are those variables, which cannot be changed by other variables being measured. For instance, age, among others. On the other hand, dependent variables are those variables that change with factors affecting them. For instance, quality of service, among others. In essence, independent variables can change dependent variables.

Levels of measurement of both independent and dependent variables

In statistical analysis, there are four levels of measurements. These include ordinal, ratio, nominal and interval. Usually, only ordinal or nominal data in research can be considered as either numeric or string (alphanumeric).On the other hand, scale variables can only contain numbers. Level of measurement is important in statistical analysis because it ensures that variables are assigned to their correct level. It should also be noted that level of measurements are usually nominal or continuous. While independent variables are usually considered as continuous, dependent variables are considered as nominal. In essence, level of measurement must be utilized in statistical analysis to achieve desired results (Bilheimer & Klein, 2010).

Rational for classification of the variables

Classification of variables is essential because it enabled researchers to manipulate data as required. In cases where dependent variables are nominal while independent variables are continuous, it is possible to perform analysis on nursing data to come up with desired links. Additionally, when all variables are continuous, analysis becomes complex.

Considerations for analyzing data related to each variable based on its level of measurement

During data analysis, it should be noted that each variable has its correct measurement level. This can be nominal, scale, or ordinal, among others. It should also be noted that commands in SPSS usually rely on measurement levels. For instance, use of chart builders and custom tables can only be achieved by assigning correct measurement levels to the variables. Therefore, it is critical for researchers to declare measurement levels for better commands in SPSS (Granberg-Rademacker, 2010).

Advantages or challenges, which might be encountered in statistical analysis of each variable

Statistical analysis is essential because it enables researchers to explore their ideas through analysis. Additionally, statistical analysis has the advantage of enabling researchers to manipulate or model variables for testing of new or evidence based practices. However, it should be noted that statistical analysis has its challenges. Data acquisition and analysis presents challenges in assigning of correct measurement levels, as well as in choosing of correct variables for analysis.

Conclusion

Measurement level is an essential property, which is assigned to variables in statistical analysis. Whenever correct measurement levels are assigned to variables, SPSS commands are taken appropriately. This reduces the complexity of data analysis and therefore improves nursing research.

References

Bilheimer, L. T. & Klein, R. J. (2010). Data and measurement issues in the analysis of health disparities. Health Services Research, 45(5), 14891507.

Granberg-Rademacker, J. S. (2010). An algorithm for converting ordinal scale measurement data to interval/ratio scale. Educational & Psychological Measurement, 70(1), 74-90.

Polit, D. (2010). Statistics and data analysis for nursing research (2^nd ed.). Upper Saddle River, NJ: Pearson Education Inc.

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