On Jul 4, 2013, at 14:38 , Dániel Kehl wrote: > Dear Prof Ripley, > > could you be just a little more specific?
He'll likely find that difficult. It's sort of like if you had data like this 25 75 75 25 25 75 and did a trend test. The trend test _assumes_ that the effect is increasing, and constructs a test based on the slope. Since it it isn't increasing, the effect isn't found: > prop.trend.test(c(25,75,25),c(100,100,100)) Chi-squared Test for Trend in Proportions data: c(25, 75, 25) out of c(100, 100, 100) , using scores: 1 2 3 X-squared = 0, df = 1, p-value = 1 However, if you fit the implied model, you get > score <- 1:3 > summary(glm(cbind(c(25,75,25),c(75,25,75)) ~ score, binomial)) Call: glm(formula = cbind(c(25, 75, 25), c(75, 25, 75)) ~ score, family = binomial) Deviance Residuals: 1 2 3 -3.486 6.768 -3.486 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -3.365e-01 3.098e-01 -1.086 0.277 score -2.548e-16 1.434e-01 0.000 1.000 (Dispersion parameter for binomial family taken to be 1) Null deviance: 70.115 on 2 degrees of freedom Residual deviance: 70.115 on 1 degrees of freedom AIC: 88.444 Number of Fisher Scoring iterations: 3 where the z-value for the score coefficient is 0, but the residual deviance reveals that the model doesn't fit the data. > > Thanks a lot > daniel > ________________________________________ > Feladó: Prof Brian Ripley [rip...@stats.ox.ac.uk] > Küldve: 2013. július 4. 14:14 > To: Dániel Kehl > Cc: r-help > Tárgy: Re: [R] polr? > > On 04/07/2013 12:59, Dániel Kehl wrote: >> Dear R users, >> >> I have a dataset with two ordered variables, tr_x1 and tr_y1. A crosstable >> of them can bee seen below. >> >> tr_x1 >> tr_y1 -1 0 1 >> -1 629 100 629 >> 0 1396 4353 1443 >> 1 668 126 655 >> >> It is clear that if tr_x1 is 0, it has an effect on tr_y1. A chi-square >> statistic is clearly showing this with a low p-value. >> Is there a regression-based method you would offer? I tried polr from MASS >> package but without finding a significant coefficient, because the columns >> for tr_x1 and tr_y1 are similar. > > Your mistake is testing coefficients, not overall fit. > >> Thank you for your help! >> >> daniel >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> 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. >> > > > -- > Brian D. Ripley, rip...@stats.ox.ac.uk > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > ______________________________________________ > R-help@r-project.org mailing list > 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 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list 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.