This example shows that the default for centile is to compute a C.I. Will compute an exact 95 per cent confidence interval for the median of income. Option l (letter l), or level, may be used to obtain a confidence level that is different from the default.Ĭ.I. Note that a number of different estimation procedures for proportions are available, such as the Agresti-Coull confidence interval.įor counts, use the poisson option (again, see Stata's help for more on this). for the sample mean of a metric variable.Īssumes that gender is a binary variable with values 0 and 1 it will display the proportion of observations coded '1' and the exact 95 per cent confidence interval for this proportion. This example shows that the default for ci is to compute a C.I. Will compute a 95 per cent confidence interval for the mean of income. Statistics & Data Analysis 50: 775–782, is available via option bonett. (2006), Approximate confidence interval for standard deviation of nonnormal distributions, Computational

An alternative version of the interval proposed by Bonett, D. As an example, useĪnd add option, sd for the standard deviation. In contrast to earlier versions, procedure ci now also offers computation of a confidence interval for the variance (or the standard deviation) of a variable. The confidence interval computed is an exact interval based on the binomial distribution several other intervals are available which may requested via the appropriate option. Note that the variable(s) to be analyzed must consist of values 0 and 1 only, and the procedure will compute the confidence interval for the proportion with value '1'. Will compute a 95 per cent confidence interval for variable gender. With count data, option poisson should be added. Request a different confidence level with option level(#), with # being replaced by, say, 90, 99, or whatever you like. Note that all command that follow permit varlists, that is, you can request confidence intervals (of the same type) for several variables. With version 14, some changes have been introduced: Command ci has to be accompanied by a keyword that indicates what kind of confidence interval is requested. On the other hand, you may easily do some rounding on your own. For instance, frequently the results displayed are too exact you will not present means or C.I.s with six decimal values to any audience. Of course, you may also use the format command to influence the decimals in the output for other reasons. If such strange results occur, change the display format of the respective variable, either via the Variable Manager available in more recent versions of Stata or via commands such as format income %10.4f this means that variable income will be displayed with an overall width of 10, among which 4 decimal values. It does not happen always under such circumstances as yet I could not find out the exact circumstances that cause such strange behaviour. This seems to happen when the display format of a variable is defined in a way that no decimal values are given (which may seem perfectly ok if a variable has no decimal values). standard errors of 0, or integer values for the C.I., which is a very rare thing to occur. Warning: The following procedures may give strange results, i.e. On the other hand, a few special estimation procedures are available particularly concerning proportions. Note, however, that the complex estimation procedures mentioned in the previous entry (with two of them outlined in more detail in the next two entries) are not available. In addition to the procedures described in the previous entry, Stata offers some commands for the estimation of confidence intervals for means, proportions, counts, and percentiles (plus, as of version 14, for variances and standard deviations). Multiple Imputation: Analysis and Pooling Steps.Confidence Intervals with ci and centile.Changing the Look of Lines, Symbols etc.

Stata confidence interval