Exact(2)
If the current C.D.C. estimation of prevalence is correct, then there will be an awful lot of adult autistics who need lifetime support and care.
If so, the estimated prevalence is correct.
Similar(6)
Essentially the apparent (or 'naive') prevalence is corrected for the detection probability and an unbiased estimate of the number of vector individuals occupied by the pathogen, i.e. estimated prevalence, is obtained.
Using the estimates of sensitivity and specificity derived from the validation study in the general population sample, the crude prevalence was corrected for the impact of misclassification and 95% CI was calculated.
The prevalences were corrected by the population probability weights (pweights) calculated as follows: 1/(n of sampled animals/N of animals in the forest district).
In other words, if the hypothesis that autism is a constant-prevalence condition is correct, a snapshot-based prevalence vs. birth year plot should be essentially a flat line with equal prevalence at all ages – albeit a line whose absolute value rises with each new report as diagnosis continues to improve.
However, if the constant-prevalence hypothesis is correct, even if some of the older children remain undiagnosed and the snapshot-based prevalence vs. birth year plot is not a perfect flat line, it still should have a substantially flatter slope than a constant-age-tracking-based prevalence vs. birth year plot covering the same time interval.
The results of this investigation suggest that, if the assumption of non-differential misclassification and constant prevalence of outcome is correct, the relative risks for health outcomes may be becoming slightly more biased towards the null with each contact.
Related(1)
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com