how to calculate confidence interval for incidence rate?
315958
To calculate the confidence interval, multiply the estimated rate by the confidence factor associated with the number of events on which the rate is based.
245669
['Estimating the standard deviation, σ, of the sample data.', 'Multiplying that number by three.', 'Adding (3 x σ to the average) for the UCL and subtracting (3 x σ from the average) for the LCL.']
253922
['Find the mean of the set of data.', 'Subtract each number from the mean.', 'Square the result.', 'Add the results together.']
188771
['Frequency (count) The number of occurrences of the corresponding code (value).', 'Percent Percent occurrence of the code (count divided by total number of observations.', 'Valid Percent Percent occurrence of the code: count divided by the total number of valid (=non-missing) observations. [']
928424
The formula for the 95% confidence interval using the normal approximation is p ±1.96√[p(1-p)/n], where p is the proportion and n is the sample size. Thus, for P=0.20 and n=100, the confidence interval would be ±1.96√[0.20(1-0.20)/100], or 0.20±0.078.
892189
To do this, divide the frequency by the total number of results and multiply by 100. In this case, the frequency of the first row is 1 and the total number of results is 10. The percentage would then be 10.0.
350469
Rate ratios are closely related to risk ratios, but they are computed as the ratio of the incidence rate in an exposed group divided by the incidence rate in an unexposed (or less exposed) comparison group. The rate in those NOT using hormones was 60 / 51,477.5 = 116.6 per 100,000 person-years.
541784
['Step 1: Calculate the mean of the data—this is μ in the formula.', 'Step 2: Subtract the mean from each data point. ... ', 'Step 3: Square each deviation to make it positive.', 'Step 4: Add the squared deviations together.', 'Step 5: Divide the sum by the number of data points in the population.']
50325
To calculate the confidence interval, we must find p′, q′. p′ = 0.842 is the sample proportion; this is the point estimate of the population proportion. Since the requested confidence level is CL = 0.95, then α = 1 – CL = 1 – 0.95 = 0.05 (α2) = 0.025.
254264
Because you want a 95% confidence interval, your z*-value is 1.96. Suppose you take a random sample of 100 fingerlings and determine that the average length is 7.5 inches; assume the population standard deviation is 2.3 inches. This means. Multiply 1.96 times 2.3 divided by the square root of 100 (which is 10).
223490
To compute the 95% confidence interval, start by computing the mean and standard error: M = (2 + 3 + 5 + 6 + 9)/5 = 5. σM = = 1.118. Z.95 can be found using the normal distribution calculator and specifying that the shaded area is 0.95 and indicating that you want the area to be between the cutoff points.
1430409
['Multiply the adjusted proportion by 1 – the adjusted proportion. .78 * ( 1-.78 )=.17.', 'Divide the result of step a by the adjusted sample size from step 2. .17/ 54 = .0032.', 'Take the square root of the value from step b. 0032= .056.']
1465729
['Determine the confidence level and find the appropriate z*-value. Refer to the above table.', 'Find the sample proportion. ... ', 'Take the difference between the sample proportions,', 'Find. ... ', 'Multiply z* times the result from Step 4. ... ', 'Take.']
992900
The 95% confidence interval on the difference between means extends from -4.267 to 0.267. The calculations are somewhat more complicated when the sample sizes are not equal.
1172720
['Compute the square of the difference between each value and the sample mean.', 'Add those values up.', 'Divide the sum by n-1. This is called the variance.', 'Take the square root to obtain the Standard Deviation.']
1163923
['To calculate the sample standard deviation, use formulas in this category: STDEV. S, STDEVA, and STDEV.', 'To calculate the standard deviation for an entire population, use formulas in this category: STDEV. P, STDEVPA, and STDEVP.']
495703
Calculate the mean. Subtract the mean from each observation. ... Divide this total by the number of observations (variance, S2). Use the positive square root (standard deviation, S).