Nursing Statistics Sampling and Results: Thesis

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In interacting, factors may also modify each other:

nurse who might return to work for a higher salary might decide to do so only later when her children are older. The incentive of salary is therefore modified by the factor of young children.

The table is significantly complicated by the inclusion of more than two factors:

Any combination of the factors could result in the majority of nurses returning to work. Individually, each nurse has his or her own motivations for doing so.

The iterative proportional fitting procedure can be used to calculate expected frequencies.

Note: Specifically, the indication of this study is that nurses would return to work were certain factors in the work situation to change. Specifically, the highest frequencies are assigned to work load and hours. These are also the two most common factors in causing burnout and stress in the profession. Concomitantly, if inactive nurses were to return to work under better conditions in this regard, the workload, stress, and burnout factors can also be significantly reduced in the nursing profession in general.

3. PURPOSE of STATISTICAL TEST

Crosstabulation is one of the simplest statistical tests available for analyzing and comparing statistical data. It lends itself well to indicating relationships and frequencies between data factors.

Purpose of Crosstabulation for Study

Determining the factors that could potentially influence nurses to return to work.

Indicating the importance of various influencing factors for both inactive nurses and by association for active nurses:

In this regard, the causes of stress and burnout resulting in nurses leaving the profession are particularly important; removing these will not only encourage inactive nurses to return to their professions, but also discourage active nurses from leaving.

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The data can be summarized clearly in a multi-way frequency table:

This enables a clear delineation and comparison of the data, providing a wider perspective than would otherwise be possible.

Log-Linear indicates a sophisticated analysis of frequency tables. This can be used to test the interaction of the various factors and their statistical significance:

Nurses may for example experience the highest frequency of likelihood to return to nursing if various factors are in favor of their doing so. This result can then be used to predict a more accurate number of returns when variables are modified.

Correspondence analysis measure the correspondence between factors presented in the table. This can be used in concomitance with the log-linear results in order to further increase the accuracy of predictions. Note: if the most significant factors in nursing can be modified, a significant mitigation of nursing shortage can be orchestrated......

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