Dear Peter, Yes, It is a technical issue and a matter of diddling around. And I agree with your comment regarding the 2 observations. I have several thousands variance estimates for which I need to compute the sample sizes automatically. Using try statements is typically the last thing I would like to resort too. Is there an alternative implementation of power.t.test on CRAN which could the diddling for me and return plausible sample sizes i.e. integers. best regards Witek On Fri, 4 Oct 2019 at 16:28, peter dalgaard <pdalgd at gmail.com> wrote:> > This is mainly a technical issue with uniroot trying to go outside of its interval: (2, 1e7) > > It is fairly easy to find an approximate solution by diddling a little by hand: > > > power.t.test(delta = 0.5849625, sd=0.01, n=1.04, sig.level=0.05)$power > [1] 0.8023375 > > Notice, however, that 1.04 observations in each group makes no sense at all. In order to actually do a t-test you need at least 2 observations per group (since we assume equal group sizes) or you have no variance estimate. Already at sd=0.1, you are crossing the n=2 border, so for any smaller sd, you will just get higher power with n=2. (Also, anything with single-digit degrees of freedom for variance is probably expecting rather much regarding to Gaussian distribution of your data.) > > -pd > > > On 4 Oct 2019, at 14:30 , Witold E Wolski <wewolski at gmail.com> wrote: > > > > Hi, > > > > power.t.test works for some range of input parameters but fails otherwise. > > > >> power.t.test(delta = 0.5849625, sd=0.1, power=0.8, sig.level=0.05)$n > > [1] 1.971668 > >> power.t.test(delta = 0.5849625, sd=0.05, power=0.8, sig.level=0.05)$n > > [1] 1.620328 > >> power.t.test(delta = 0.5849625, sd=0.01, power=0.8, sig.level=0.05)$n > > Error in uniroot(function(n) eval(p.body) - power, c(2, 1e+07), tol = tol, : > > did not succeed extending the interval endpoints for f(lower) * f(upper) <= 0 > > In addition: Warning message: > > In qt(sig.level/tside, nu, lower.tail = FALSE) : NaNs produced > > > > I guessing that sd is very small compared with delta, hence the > > problem. But what are allowed values (ratios) of delta and sd? > > > > Best > > Witek > > > > > > > > > > > > > > -- > > Witold Eryk Wolski > > > > ______________________________________________ > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Office: A 4.23 > Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com > > > > > > > > >-- Witold Eryk Wolski
"...plausible sample sizes i.e. integers." ?? f(...) = function that returns a real. ceiling(f(...)) = function that returns an integer. The problem is the "plausible" part. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, Oct 15, 2019 at 3:11 AM Witold E Wolski <wewolski at gmail.com> wrote:> Dear Peter, > > Yes, It is a technical issue and a matter of diddling around. And I > agree with your comment regarding the 2 observations. > I have several thousands variance estimates for which I need to > compute the sample sizes automatically. Using try statements is > typically the last thing I would like to resort too. > Is there an alternative implementation of power.t.test on CRAN which > could the diddling for me and return plausible sample sizes i.e. > integers. > > best regards > Witek > > On Fri, 4 Oct 2019 at 16:28, peter dalgaard <pdalgd at gmail.com> wrote: > > > > This is mainly a technical issue with uniroot trying to go outside of > its interval: (2, 1e7) > > > > It is fairly easy to find an approximate solution by diddling a little > by hand: > > > > > power.t.test(delta = 0.5849625, sd=0.01, n=1.04, sig.level=0.05)$power > > [1] 0.8023375 > > > > Notice, however, that 1.04 observations in each group makes no sense at > all. In order to actually do a t-test you need at least 2 observations per > group (since we assume equal group sizes) or you have no variance estimate. > Already at sd=0.1, you are crossing the n=2 border, so for any smaller sd, > you will just get higher power with n=2. (Also, anything with single-digit > degrees of freedom for variance is probably expecting rather much regarding > to Gaussian distribution of your data.) > > > > -pd > > > > > On 4 Oct 2019, at 14:30 , Witold E Wolski <wewolski at gmail.com> wrote: > > > > > > Hi, > > > > > > power.t.test works for some range of input parameters but fails > otherwise. > > > > > >> power.t.test(delta = 0.5849625, sd=0.1, power=0.8, sig.level=0.05)$n > > > [1] 1.971668 > > >> power.t.test(delta = 0.5849625, sd=0.05, power=0.8, sig.level=0.05)$n > > > [1] 1.620328 > > >> power.t.test(delta = 0.5849625, sd=0.01, power=0.8, sig.level=0.05)$n > > > Error in uniroot(function(n) eval(p.body) - power, c(2, 1e+07), tol > tol, : > > > did not succeed extending the interval endpoints for f(lower) * > f(upper) <= 0 > > > In addition: Warning message: > > > In qt(sig.level/tside, nu, lower.tail = FALSE) : NaNs produced > > > > > > I guessing that sd is very small compared with delta, hence the > > > problem. But what are allowed values (ratios) of delta and sd? > > > > > > Best > > > Witek > > > > > > > > > > > > > > > > > > > > > -- > > > Witold Eryk Wolski > > > > > > ______________________________________________ > > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > > and provide commented, minimal, self-contained, reproducible code. > > > > -- > > Peter Dalgaard, Professor, > > Center for Statistics, Copenhagen Business School > > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > > Phone: (+45)38153501 > > Office: A 4.23 > > Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com > > > > > > > > > > > > > > > > > > > > > -- > Witold Eryk Wolski > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]
You don't really want the diddling, since it gives meaningless values anyway... For a pragmatic strategy, how about this?: (a) calculate the power at n=2, if bigger than target power, done, else (b) calculate n to reach target power, now guaranteed to have n > 2. Round upwards. Peter D.> On 15 Oct 2019, at 12:07 , Witold E Wolski <wewolski at gmail.com> wrote: > > Dear Peter, > > Yes, It is a technical issue and a matter of diddling around. And I > agree with your comment regarding the 2 observations. > I have several thousands variance estimates for which I need to > compute the sample sizes automatically. Using try statements is > typically the last thing I would like to resort too. > Is there an alternative implementation of power.t.test on CRAN which > could the diddling for me and return plausible sample sizes i.e. > integers. > > best regards > Witek > > On Fri, 4 Oct 2019 at 16:28, peter dalgaard <pdalgd at gmail.com> wrote: >> >> This is mainly a technical issue with uniroot trying to go outside of its interval: (2, 1e7) >> >> It is fairly easy to find an approximate solution by diddling a little by hand: >> >>> power.t.test(delta = 0.5849625, sd=0.01, n=1.04, sig.level=0.05)$power >> [1] 0.8023375 >> >> Notice, however, that 1.04 observations in each group makes no sense at all. In order to actually do a t-test you need at least 2 observations per group (since we assume equal group sizes) or you have no variance estimate. Already at sd=0.1, you are crossing the n=2 border, so for any smaller sd, you will just get higher power with n=2. (Also, anything with single-digit degrees of freedom for variance is probably expecting rather much regarding to Gaussian distribution of your data.) >> >> -pd >> >>> On 4 Oct 2019, at 14:30 , Witold E Wolski <wewolski at gmail.com> wrote: >>> >>> Hi, >>> >>> power.t.test works for some range of input parameters but fails otherwise. >>> >>>> power.t.test(delta = 0.5849625, sd=0.1, power=0.8, sig.level=0.05)$n >>> [1] 1.971668 >>>> power.t.test(delta = 0.5849625, sd=0.05, power=0.8, sig.level=0.05)$n >>> [1] 1.620328 >>>> power.t.test(delta = 0.5849625, sd=0.01, power=0.8, sig.level=0.05)$n >>> Error in uniroot(function(n) eval(p.body) - power, c(2, 1e+07), tol = tol, : >>> did not succeed extending the interval endpoints for f(lower) * f(upper) <= 0 >>> In addition: Warning message: >>> In qt(sig.level/tside, nu, lower.tail = FALSE) : NaNs produced >>> >>> I guessing that sd is very small compared with delta, hence the >>> problem. But what are allowed values (ratios) of delta and sd? >>> >>> Best >>> Witek >>> >>> >>> >>> >>> >>> >>> -- >>> Witold Eryk Wolski >>> >>> ______________________________________________ >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >> >> -- >> Peter Dalgaard, Professor, >> Center for Statistics, Copenhagen Business School >> Solbjerg Plads 3, 2000 Frederiksberg, Denmark >> Phone: (+45)38153501 >> Office: A 4.23 >> Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com >> >> >> >> >> >> >> >> >> > > > -- > Witold Eryk Wolski-- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
>>>>> Bert Gunter >>>>> on Tue, 15 Oct 2019 07:41:35 -0700 writes:> "...plausible sample sizes i.e. integers." > ?? > f(...) = function that returns a real. > ceiling(f(...)) = function that returns an integer. > The problem is the "plausible" part. Actually, power.t.test() does not return an integer for 'n' typically in any case. I found that it's actually quite easy to power.t.test() do the diddling for us and return a number between 1 and 2. What you do with that number is your decision, but formally it solves the root finding problem :> (ptt1 <- power.t.test(delta = 0.6, sd=0.00001, power=0.9 , sig.level=0.05))Two-sample t test power calculation n = 1.004283 delta = 0.6 sd = 1e-05 sig.level = 0.05 power = 0.9 alternative = two.sided NOTE: n is number in *each* group -------------------- As the change is small, and I see that Witold has good reasons to prefer this to wrapping everything in try(.) or (better) tryCatch(.), I propose to commit the change after a bit more testing. Martin > Cheers, > Bert > Bert Gunter > "The trouble with having an open mind is that people keep coming along and > sticking things into it." > -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) > On Tue, Oct 15, 2019 at 3:11 AM Witold E Wolski <wewolski at gmail.com> wrote: >> Dear Peter, >> >> Yes, It is a technical issue and a matter of diddling around. And I >> agree with your comment regarding the 2 observations. >> I have several thousands variance estimates for which I need to >> compute the sample sizes automatically. Using try statements is >> typically the last thing I would like to resort too. >> Is there an alternative implementation of power.t.test on CRAN which >> could the diddling for me and return plausible sample sizes i.e. >> integers. >> >> best regards >> Witek >> >> On Fri, 4 Oct 2019 at 16:28, peter dalgaard <pdalgd at gmail.com> wrote: >> > >> > This is mainly a technical issue with uniroot trying to go outside of >> its interval: (2, 1e7) >> > >> > It is fairly easy to find an approximate solution by diddling a little >> by hand: >> > >> > > power.t.test(delta = 0.5849625, sd=0.01, n=1.04, sig.level=0.05)$power >> > [1] 0.8023375 >> > >> > Notice, however, that 1.04 observations in each group makes no sense at >> all. In order to actually do a t-test you need at least 2 observations per >> group (since we assume equal group sizes) or you have no variance estimate. >> Already at sd=0.1, you are crossing the n=2 border, so for any smaller sd, >> you will just get higher power with n=2. (Also, anything with single-digit >> degrees of freedom for variance is probably expecting rather much regarding >> to Gaussian distribution of your data.) >> > >> > -pd >> > >> > > On 4 Oct 2019, at 14:30 , Witold E Wolski <wewolski at gmail.com> wrote: >> > > >> > > Hi, >> > > >> > > power.t.test works for some range of input parameters but fails >> otherwise. >> > > >> > >> power.t.test(delta = 0.5849625, sd=0.1, power=0.8, sig.level=0.05)$n >> > > [1] 1.971668 >> > >> power.t.test(delta = 0.5849625, sd=0.05, power=0.8, sig.level=0.05)$n >> > > [1] 1.620328 >> > >> power.t.test(delta = 0.5849625, sd=0.01, power=0.8, sig.level=0.05)$n >> > > Error in uniroot(function(n) eval(p.body) - power, c(2, 1e+07), tol >> tol, : >> > > did not succeed extending the interval endpoints for f(lower) * >> f(upper) <= 0 >> > > In addition: Warning message: >> > > In qt(sig.level/tside, nu, lower.tail = FALSE) : NaNs produced >> > > >> > > I guessing that sd is very small compared with delta, hence the >> > > problem. But what are allowed values (ratios) of delta and sd? >> > > >> > > Best >> > > Witek >> > > >> > > -- >> > > Witold Eryk Wolski >> > > >> > >> > -- >> > Peter Dalgaard, Professor, >> > Center for Statistics, Copenhagen Business School >> > Solbjerg Plads 3, 2000 Frederiksberg, Denmark >> > Phone: (+45)38153501 >> > Office: A 4.23 >> > Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com >> >> -- >> Witold Eryk Wolski