Abstract
The use of Statistical Hypothesis Testing procedure to determine type I and type II errors was linked to the measurement of sensitivity and specificity in clinical trial test and experimental pathogen detection techniques. A theoretical analysis of establishing these types of errors was made and compared to determination of False Positive, False Negative, True Positive and True Negative. Experimental laboratory detection methods used to detect Cryptosporidium spp. were used to highlight the relationship between hypothesis testing, sensitivity, specificity and predicted values. The study finds that, sensitivity and specificity for the two laboratory methods used for Cryptosporidium detection were low hence lowering the probability of detecting a “false null hypothesis” for the presence of cryptosporidium in the water samples using either Microscopic or PCR. Nevertheless, both procedures for cryptosporidium detection had higher “true negatives” increasing its probability of failing to reject a “true null hypothesis” with specificity of 1.00 for both Microscopic and PCR laboratory detection methods.
Highlights
Measuring the effectiveness of procedures and methods has over the years received vast consideration
It helps to estimate the recovery rates for pathogen detections. These terms have been seen as an independent for scientific procedural measurements for experiments; its links to the measurement of the Null Hypothesis Testing Procedure (NHTP) give the backbone of statistical interpretation of hypothesis testing results and the needed theoretical background
Water samples were transported to the Biochemistry Department of Kwame Nkrumah University of Science and Technology (KNUST) under optimal conditions and processed to obtain purified oocytes using immuno-magnetic separation (IMS)
Summary
In clinical and laboratory test, the imperative answers seeking is whether the accepted protocol or diagnostic procedure test is either sensitive enough to detect the presence of a disease/pathogen in a contaminated sample or is the test specific enough to indicate the absence of a diseases or pathogen in samples which are not contaminated with the pathogen. Definition of sensitivity is the probability measuring the likelihood for a test to pick up the presence of a disease/pathogen, alternatively, a true positive is recorded when a procedure reflects the presence of pathogen in a contaminated sample. We define specificity as the probability of measuring the likelihood for a test to pick up the absence of a disease/pathogen, alternatively, a true negative is recorded when a procedure reflects the absence of a pathogen when the sample is not contaminated [1]. A false positive occurs when the test reports a positive result for a person who is disease free or a positive result for a pathogen free sample, whereas a false negative occurs when the test reports a negative result for a person who has the disease or negative result for a pathogen infested sample [3]
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