R/omegaSqDist.R In userfriendlyscience: Quantitative Analysis Made Accessible

Documented in domegaSqpomegaSqqomegaSqromegaSq

```# domegaSq <- function(x, df1, df2, populationOmegaSq = 0) {
#   if (populationOmegaSq != 0) {
#     cat0("Noncentrality parameters not implemented yet, sorry!\n");
#   }
#   ### Return density for given omega squared
#   return(df(convert.omegasq.to.f(x, df1, df2), df1, df2));
# }

pomegaSq <- function(q, df1, df2, populationOmegaSq = 0, lower.tail=TRUE) {
if (populationOmegaSq != 0) {
cat0("Noncentrality parameters not implemented yet, sorry!\n");
}
### Return p-value for given omega squared
return( pf(convert.omegasq.to.f(q, df1, df2), df1, df2, lower.tail=lower.tail) );
}

qomegaSq <- function(p, df1, df2, populationOmegaSq = 0, lower.tail=TRUE) {
if (populationOmegaSq != 0) {
cat0("Noncentrality parameters not implemented yet, sorry!\n");
}
### Return omega squared for given p-value
return(convert.f.to.omegasq(qf(p, df1, df2, lower.tail=lower.tail), df1, df2));
}

romegaSq <- function(n, df1, df2, populationOmegaSq = 0) {
if (populationOmegaSq != 0) {
cat0("Noncentrality parameters not implemented yet, sorry!\n");
}
### Return random omega squared value(s)
return(convert.f.to.omegasq(rf(n, df1, df2), df1, df2));
}

domegaSq <- function(x, df1, df2, populationOmegaSq = 0) {
return(df(convert.omegasq.to.f(x, df1, df2), df1, df2,
ncp = convert.omegasq.to.f(populationOmegaSq, df1, df2)));
}

# pomegaSq <- function(q, df1, df2, populationOmegaSq = 0, lower.tail=TRUE) {
#   if (populationOmegaSq != 0) {
#     cat0("Noncentrality parameters not implemented yet, sorry!\n");
#   }
#   ### Return p-value for given omega squared
#   return( pf(convert.omegasq.to.f(q, df1, df2), df1, df2,
#              lower.tail=lower.tail,
#              ncp = convert.omegasq.to.f(populationOmegaSq, df1, df2)) );
# }
#
# qomegaSq <- function(p, df1, df2, populationOmegaSq = 0, lower.tail=TRUE) {
#   if (populationOmegaSq != 0) {
#     cat0("Noncentrality parameters not implemented yet, sorry!\n");
#   }
#   ### Return omega squared for given p-value
#   return(convert.f.to.omegasq(qf(p, df1, df2,
#                                  lower.tail=lower.tail,
#                                  ncp = convert.omegasq.to.f(populationOmegaSq, df1, df2)),
#                               df1, df2));
# }
#
# romegaSq <- function(n, df1, df2, populationOmegaSq = 0) {
#   if (populationOmegaSq != 0) {
#     cat0("Noncentrality parameters not implemented yet, sorry!\n");
#   }
#   ### Return random omega squared value(s)
#   return(convert.f.to.omegasq(rf(n, df1, df2,
#                                  ncp = convert.omegasq.to.f(populationOmegaSq, df1, df2)),
#                               df1, df2));
# }
```

Try the userfriendlyscience package in your browser

Any scripts or data that you put into this service are public.

userfriendlyscience documentation built on May 2, 2019, 1:09 p.m.