Bio-Statistics Research Activities, Whether Clinical Term Paper

Pages: 5 (2419 words)  ·  Bibliography Sources: 1+  ·  Level: College Senior  ·  Topic: Education - Mathematics

SAMPLE EXCERPT:

[. . .] In other words, the authors did not build a medical or healthcare-based paradigm for the study. Following a well-defined research question the research investigators' task is to follow-up with a statement of a testable null hypothesis or hypotheses. The null form of the hypothesis is required in order for the proper application of a statistical data analysis tool to be implemented (Ohlson, 1998). Simply stating that an attempt to "confer" that an insulin deficiency might or might not affirm a "predisposition to complications" is not adhering to proper scientific research protocol with respect to a needed testable null hypothesis (Van Dalen, 1964).

Another important criteria of effective research are the use of an appropriate sampling procedure. Sampling alone can skew testing results, infuse uncontrollable error into statistical processes, and violate the empirical premise under which the medical process is being conducted. In order for accurate conclusions to be drawn about any medical procedure there must exist and adequate sample size as well as to employ the appropriate sampling procedure. In the arena Van de Berghe and his research colleagues were on target in randomly assigning patients to either the treatment or control situation. Although the research investigators chose to use the entire population as their sample this procedure can be described as a probability sampling as the sample is excessive (1548 participants). If the researchers had opted to take a random sample from the 1548 participants the procedure would likely have had delivered the same results -- provided the sample drawn from the overall population was large enough (Ferguson, 1966). Wherein they fell short was advising the reader as to possible unequal cell frequencies for the measurement variables they finally identified in the Outcome Section. Knowledge of the unequal cell frequency situation, and with respect to topical demographics, is important when the investigator chooses the appropriate statistical tool to analyze the measurement data. The research investigators might well have also informed the reader as to the type of randomization that was employed; i.e., simple random, stratified, cluster random, or equal probability random sampling.

Journal Article Research Critique -- Non-Probability Sampling

Thompson, David M., Kozak, Sharon E. And Sheps, Sam (1999). Insulin adjustment by a diabetes nurse educator improves glucose control in insulin-requiring diabetic patients: A randomized trial. CMAJ, 161(8):959-62

In keeping with the format used to evaluate and critique the Van de Berghe, et al. article on insulin therapy the article by Thompson, Kozak and Sheps will follow along the same lines. First the authors of the second article, unlike those of the first, did present the reader with a research question, even though it was in the form of a declarative statement. That is, the authors took a pre-investigative stand and stated that their independent variable would have an effect on the dependent variable [i.e., insulin adjustment according to advice provided by telephone by a diabetes nurse educator (treatment variable) could lead to better glucose control, as indicated by level of glycated hemoglobin (measurement variable]. Wherein the authors further adhered to prudent research formatting was in their statement of a testable null hypothesis. Whenever a statistical tool is used to analyze measurement data the requirement of stating a null hypothesis must be maintained. With respect to sampling procedure requirements the authors chose a randomized assignment procedure with a non-probability sampling method. That is, the participants of the study were randomly assigned to a standard insulin care group vs. A telephone contact nurse care group. What is significantly important with this particular study is the author's use of a calculation to determine the size of the sample initially needs to garner the expected results of a decrease of one standard deviation. Their calculations determined that they needed 21 patients. When statistical procedures are employed to determine the sample size needed when probability sampling is not possible the calculations greatly advance the reduction of error generally associated with non-probability research studies. However, regardless of the statistical procedure used to set sampling limits for non-probability studies more error and bias reduction takes place when probability sampling occurs; i.e., the smaller representing a larger whole. The authors of the second article might possibly infer from the results of their research investigation to a general larger population but they will have to do so with a great deal caution. The authors are, however, in a strong position to recommend replication to determine whether of not the results from their study can be maintained over a larger population. If the results can they the study has a great deal of merit. If, however, replication by using a probability sampling procedure produces different results then one can conclude the results of the original non-probability sampling study are only applicable to those participating in the study and not to the larger population of insulin users. Studies that have no general applicability are not necessarily just important to those who conducted the original research, but they often spur future research endeavors by others.

References

Ferguson, Geroge A. 1966. Statistical Analysis in Psychology and Education. New York:

McGraw-Hill Book Company

Ohlson, E.L 1998. Best-Fit Statistical Procedures, ACTS Testing Labs. Chicago Thompson, David M., Kozak, Sharon E. And Sheps, Sam (1999). Insulin adjustment by a diabetes nurse educator improves glucose control in insulin-requiring diabetic patients: A randomized trial. CMAJ, 161(8):959-62

Van Dalen, Debold B. (1966). Understanding educational research. New York: McGraw-Hill

Book Company.

Van de Berghe et al.… [END OF PREVIEW]

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