Description Usage Arguments Details Value References See Also Examples
Based on the inversion principle, parametric confidence intervals for the non-centrality parameter Delta of the F distribution are calculated. Note that we do not provide bootstrap confidence intervals here to keep the input interface simple. A positive lower (1-alpha)*100%-confidence limit for the ncp goes hand-in-hand with a significant F test at level alpha.
1 |
x |
The result of |
df1 |
The numerator degree of freedom, e.g. the number of parameters (including the intercept) of a linear regression. Only used if |
df2 |
The denominator degree of freedom, e.g. n - df1 - 1 in a linear regression. Only used if |
probs |
Error probabilites. The default c(0.025, 0.975) gives a symmetric 95% confidence interval. |
Note that, according to ?pf
, the results might be unreliable for very large F values.
A list with class cint
containing these components:
parameter
: The parameter in question.
interval
: The confidence interval for the parameter.
estimate
: The estimate for the parameter.
probs
: A vector of error probabilities.
type
: The type of the interval.
info
: An additional description text for the interval.
Smithson, M. (2003). Confidence intervals. Series: Quantitative Applications in the Social Sciences. New York, NY: Sage Publications.
1 2 3 4 5 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.