why odds ratio for case control?
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It tells us how much higher the odds of exposure is among cases of a disease compared with controls. The odds ratio compares the odds of exposure to the factor of interest among cases to the odds of exposure to the factor among controls. ... The exposure may be protective against the disease.
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When the P-value is less than 0.05 (P<0.05), the conclusion is that the two means are significantly different. Note that in MedCalc P-values are always two-sided (or two-tailed).
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No. The probability of Type 1 error is alpha -- the criterion that we set as the level at which we will reject the null hypothesis. The p value is something else -- it tells you how UNUSUAL the data are, given the assumption that the null hypothesis is true.
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The CoaguChek XS is accurate compared with the pathological method. Trained patients are able to use the CoaguChek XS in their home to provide a fast and reliable international normalized ratio (INR) result. General practitioners and patients are highly satisfied with the accuracy of the device in clinical practice.
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These genetic and environmental similarities make it easier for scientists to spot rare differences in a population group that could be related to health or disease. Such studies also can help explain why some medical conditions are more common in certain population groups.
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['The confounding factor must be associated with both the risk factor of interest and the outcome.', 'The confounding factor must be distributed unequally among the groups being compared.']
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For a Chi-square test, a p-value that is less than or equal to your significance level indicates there is sufficient evidence to conclude that the observed distribution is not the same as the expected distribution. You can conclude that a relationship exists between the categorical variables.
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The Difference Between Relative Risk and Odds Ratios. ... The basic difference is that the odds ratio is a ratio of two odds (yep, it's that obvious) whereas the relative risk is a ratio of two probabilities. (The relative risk is also called the risk ratio). Let's look at an example.
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The main aim of a sample size calculation is to determine the number of participants needed to detect a clinically relevant treatment effect. Pre-study calculation of the required sample size is warranted in the majority of quantitative studies.
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Odds Ratio (OR) is a measure of association between exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. Important points about Odds ratio: ... OR >1 indicates increased occurrence of event.
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Cohort studies are usually but not exclusively prospective, the opposite is true for case-control studies. The following notes relate cohort to case-control studies: outcome is measured after exposure. yields true incidence rates and relative risks.
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Its the kind of task which can be done by scripting, but you have to decide whether the time debugging would be worth it. Windows is not case sensitive, meaning that mixed cases are considered to be identical.
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The main strength of quantitative methods is in their usefulness in producing factual and reliable outcome data. After the effects of a given drug or treatment have been tested on a sample population, the statistic record of the observed outcomes will provide objective results generalizable to larger populations.
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Simply having a solid understanding of z-scores and how they are associated to probability allows you to easily determine the likelihood of an event occurring. Approximately 68% of values in a normally distributed variable fall between a z-score of -1 and 1. 95% of values fall between a value of -2 and 2.
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It is useful for analyzing the results of repeated independent trials, especially the probability of meeting a particular threshold given a specific error rate, and thus has applications to risk management. For this reason, the binomial distribution is also important in determining statistical significance.
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Odds Ratios and Relative Risks are often confused despite being unique concepts. ... The basic difference is that the odds ratio is a ratio of two odds (yep, it's that obvious) whereas the relative risk is a ratio of two probabilities. (The relative risk is also called the risk ratio). Let's look at an example.
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In the case of standard procedures, there is no or negligible chance of risk. It will not matter to you if you are going through ten x-rays in a year or two x-rays in a year.