search for: interquartile

Hi, I have two non-normal distributions and use interquartile ranges as a dispersion measure. Now I am looking for a test, which tests whether the interquartile ranges from the two distributions are significantly different. Any idea? Thanks, joerg [[alternative HTML version deleted]]

Hi, I am trying to show an interquartile range while grouping values using the function ddply(). So my function call now is like groupedAll <- ddply(data ,~groupColumn ,summarise ,col1_mean=mean(col1) ,col2_mode=Mode(col2) #Function I wrote for getting the mode shown...

..., At a guess, try this: iqr<-function(x) { return(paste(round(quantile(x,0.25),0),round(quantile(x,0.75),0),sep="-") } .col3_Range=iqr(datat$tenure) Jim On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> wrote: > Hi, > I am trying to show an interquartile range while grouping values using > the function ddply(). So my function call now is like > > groupedAll <- ddply(data > ,~groupColumn > ,summarise > ,col1_mean=mean(col1) > ,col2_mode=Mode(col2) #Function...

...,0.75),0),sep="-") >> } >> >> .col3_Range=iqr(datat$tenure) >> >> Jim >> >> >> >> On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> >> wrote: >> > Hi, >> > I am trying to show an interquartile range while grouping values using >> > the function ddply(). So my function call now is like >> > >> > groupedAll <- ddply(data >> > ,~groupColumn >> > ,summarise >> > ,col1_mean=mean(col1)...

...e? Also, I've found that I do not need to create indicator variables for my categorical variables when I use cph. Is this also correct? I appreciate your feedback. Thank you. ~Renee -- View this message in context: http://r.789695.n4.nabble.com/cph-nomogram-Design-RMS-package-hazard-ratio-interquartile-vs-per-unit-tp3923896p3923896.html Sent from the R help mailing list archive at Nabble.com.

...paste(round(quantile(x,0.25),0),round(quantile(x,0.75),0),sep="-") > } > > .col3_Range=iqr(datat$tenure) > > Jim > > > > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> > wrote: > > Hi, > > I am trying to show an interquartile range while grouping values using > > the function ddply(). So my function call now is like > > > > groupedAll <- ddply(data > > ,~groupColumn > > ,summarise > > ,col1_mean=mean(col1) > >...

...gt;> > .col3_Range=iqr(datat$tenure) >> > >> > Jim >> > >> > >> > >> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> >> > wrote: >> > > Hi, >> > > I am trying to show an interquartile range while grouping values >> using >> > > the function ddply(). So my function call now is like >> > > >> > > groupedAll <- ddply(data >> > > ,~groupColumn >> > > ,summarise >> > >...

...p="-") > > } > > > > .col3_Range=iqr(datat$tenure) > > > > Jim > > > > > > > > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> > > wrote: > > > Hi, > > > I am trying to show an interquartile range while grouping values > using > > > the function ddply(). So my function call now is like > > > > > > groupedAll <- ddply(data > > > ,~groupColumn > > > ,summarise > > > ,col1_mean=...

...o standardize logistic regression coefficients. I also found a very old (Thu May 12 21:50:36 CEST 2005) suggestion by Frank E Harrell (one of the colleagues who frequently contribute on this list) saying... Design doesn't implement those because they have terrible properties. Instead consider interquartile-range odds ratios (done by summary.Design by typing summary(. . .)). 1. Is this still the case, or is there any package today in R which computes some sort of standardized logistic regression coefficients widely accepted by the community? 2. Also, if anyone knows, how can I implement this inte...

...enure) >>> > >>> > Jim >>> > >>> > >>> > >>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> >>> > wrote: >>> > > Hi, >>> > > I am trying to show an interquartile range while grouping values >>> using >>> > > the function ddply(). So my function call now is like >>> > > >>> > > groupedAll <- ddply(data >>> > > ,~groupColumn >>> > > ,summa...

Hi i am doing an environmental research The equation is as follow: gam(y1 ~ x1 + s(x2) + s(x3) + s(x4), family = gaussian, fit = true) I would like to obtain the beta coefficient and 95CI of x4 (or s(x4)), what should I do? Thanks, Lung -- View this message in context: http://r.789695.n4.nabble.com/mgcv-beta-coefficient-and-95-CI-tp3320491p3320491.html Sent from the R help mailing list

...gt;> > .col3_Range=iqr(datat$tenure) >> > >> > Jim >> > >> > >> > >> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> >> > wrote: >> > > Hi, >> > > I am trying to show an interquartile range while grouping values >> using >> > > the function ddply(). So my function call now is like >> > > >> > > groupedAll <- ddply(data >> > > ,~groupColumn >> > > ,summarise >> > >...

...> > >>>> > > >>>> > > >>>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz < > michaeleartz at gmail.com> > >>>> > wrote: > >>>> > > Hi, > >>>> > > I am trying to show an interquartile range while grouping values > >>>> using > >>>> > > the function ddply(). So my function call now is like > >>>> > > > >>>> > > groupedAll <- ddply(data > >>>> > > ,~groupColumn &...

...;>> > Jim >>>> > >>>> > >>>> > >>>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz <michaeleartz at gmail.com> >>>> > wrote: >>>> > > Hi, >>>> > > I am trying to show an interquartile range while grouping values >>>> using >>>> > > the function ddply(). So my function call now is like >>>> > > >>>> > > groupedAll <- ddply(data >>>> > > ,~groupColumn >>>> > >...

...;>>> > >>> >>>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz < >>> michaeleartz at gmail.com> >>> >>>> > wrote: >>> >>>> > > Hi, >>> >>>> > > I am trying to show an interquartile range while grouping >>> values >>> >>>> using >>> >>>> > > the function ddply(). So my function call now is like >>> >>>> > > >>> >>>> > > groupedAll <- ddply(data >>> >&g...

Hi, I want to remove the outliers of my database with the following program (an observation is considered an outlier if it is bigger than second quartile + 1,5* distance interquartiles or less than second quartile - 1,5*distance interquartiles): for(i in 1:length(dados)){ q3=quantile(dados[i], probs=.75) q3=quantile(dados[i], probs=.50) q1=quantile(dados[i], probs=.25) d=q3-q1 for(i2 in 1:length(dados$quest_1)) { if (dados[i2,i] < q2-1.5*d) dados[i2,i]=NULL else if (dados[i2...

...t; > >> >>>> > >> >>>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz < >> michaeleartz at gmail.com> >> >>>> > wrote: >> >>>> > > Hi, >> >>>> > > I am trying to show an interquartile range while grouping >> values >> >>>> using >> >>>> > > the function ddply(). So my function call now is like >> >>>> > > >> >>>> > > groupedAll <- ddply(data >> >>>> > >...

...gt;>> On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz >>>>>>>>>> <michaeleartz at gmail.com> >>>>>>>>>> wrote: >>>>>>>>>>> Hi, >>>>>>>>>>> I am trying to show an interquartile range while grouping >>>>>>>>>>> values >>>>>>>>> using >>>>>>>>>>> the function ddply(). So my function call now is like >>>>>>>>>>> >>>>>>>>>&...

Hi, Is it possible to produce box-and-whisker plots given that I have the median, interquartile and 5/95th centile values, but not the data from which they come? It seems that it ought to be possible to coerce bxp to do what I want, but I can't quite see how. Thanks, Matthew -- Matthew Vernon, Research Fellow Ecology and Epidemiology Group, University of Warwick http://blogs.warwick.ac...

...gt;>> > On Tue, Apr 19, 2016 at 11:15 AM, Michael Artz >>>> >>>> > <michaeleartz at gmail.com> >>>> >>>> > wrote: >>>> >>>> > > Hi, >>>> >>>> > > I am trying to show an interquartile range while grouping >>>> >>>> > > values >>>> >>>> using >>>> >>>> > > the function ddply(). So my function call now is like >>>> >>>> > > >>>> >>>> > >...