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Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularly. Instead the prior occurrence of the event of interest is detectable only at particular times of observation, for instance, at the time of medical examination.
Hello! I am currently in graduate school earning a masters in mental health counseling. I am in a stats course at current and we are reviewing z-scores. I am a little lost because
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
The method of displaying the geographical variability of the disease on maps using different colors, shading, etc. The logic is not new, but the arrival of computers and computer g
Chi-squared distribution : It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables
Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post
Mosaic displays is the graphical display of the standardized residuals from the fitting a log-linear model to a contingency table in which the colour and outline of the mosaic's '
Consolidated Standards for Reporting Trials (CONSORT) statement : The protocol for reporting the results of the clinical trials. The core contribution of the statement comprises of
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
Confidence interval : A range of the values, calculated from the sample observations which is believed, with the particular probability, to posses the true parameter value. A 95% c
The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
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