similar to: Regression type 2, x measured with error

Hi *, is there a way to obtain some kind of p-value for a model fitted with RMA using the lmodel2 package? I know that p-values are discussed and criticized a lot and as you can image from my question I'm not very much of a statistican (only writing my bachelor thesis). As fare as I understood the confidence interval statistic correctly, a coefficient is regarded as statistically significant

Hello, I am using function lmodel2 to calculate RMA regression between life-history traits in ladybirds beetles. It works well but I am not able to plot an RMA regression line on the scatterplot of my data. I am of course unable to plot the confidence intervals. For ordinary least square regression abline(lm(x~y))works well but for RMA regression, abline(lmodel2(x~y))does not do it. If somebody

All: Any ideas on how to do variance component estimation, or at least get Expected Mean Sqaures out of the modeling commands. Thanks. Tony Tony Long Ecology and Evolutionary Biology Steinhaus Hall University of California at Irvine Irvine, CA 92697-2525 Tel: (949) 824-2562 (office) ****NOTE NEW AREA CODE**** Tel: (949) 824-5994 (lab) ****NOTE NEW AREA CODE****

hi I''m making a chess board app in Rails using the scriptaculous drag and drop stuff. A couple of questions, I am having trouble putting the chess pieces in the correct place - simply it seems that when i make somethign draggable it changes its positioning to relative - not so good for putting pieces on a board. Why is this ? Also i can''t see an OnDrop callback in the API

On Friday, 26 June 2020 10.47.13 WEST I?aki Ucar wrote: > I used bcond locally and wrongly assumed that fedpkg build would > support --with BCOND and --without BCOND. Instead, the way to activate > it is to change to "%bcond_with check" and then revert to > "%bcond_without check". The only difference with bootstrap is that > "bootstrap" is recognized

Hi, Does anybody know whether it's possible (and sensible) to calculate R^2 (or something approximating R^2) on the results of a major axis Model II regression done by lmodel2? The function lmodel2 provides an R^2 for the OLS regression only (example below), but not for major axis regression. Also, is it possible to extract major axis regression residuals? (Resid did not work on the lmodel2

Hi, Does anybody know whether it's possible (and sensible) to calculate R^2 (or something approximating R^2) on the results of a major axis Model II regression done by lmodel2? The function lmodel2 provides an R^2 for the OLS regression only (example below) Also, is it possible to extract major axis regression residuals? Many thanks, Karen Example: > Result <- lmodel2(

I am working with a RCB 2x2x3 ANCOVA, and I have noticed a difference in the calculation of sum of squares in a Type III calculation. Anova output is a follows: > Anova(aov(MSOIL~Forest+Burn*Thin*Moisture+ROCK,data=env3l),type=3) Anova Table (Type III tests) Response: MSOIL Sum Sq Df F value Pr(>F) (Intercept) 22.3682 1 53.2141 3.499e-07 *** Forest

Dear all, After a thorough research, I still find myself unable to find a function that does linear regression of 2 vectors of data using the "total least squares", also called "orthogonal regression" (see : http://en.wikipedia.org/wiki/Total_least_squares) instead of the "ordinary least squares" method. Indeed, the "lm" function has a

Hi all. Has anyone ever done a Deming Regression in R? I'm wondering if there's a simple way to do it. Thanks for all your help! -Ed -- View this message in context: http://www.nabble.com/Deming-Regression-tp17949318p17949318.html Sent from the R help mailing list archive at Nabble.com.

Dear R helpers: Thanks for the previous reply. I am using Friedman racing test. According the the book "Pratical Nonprametric Statistic" by WJ Conover, after computing the statistics, he suggested to use chi-squared or F distribution to accept or reject null hypothesis. After looking into the source code, I found that R uses chi-sqaured distribution as below: PVAL <-

Dear Rs: outer(1:3, 1:3, function(df1, df2) qf(0.95, df1, df2)) I compare this F distribution results with the table, the answers were perfect. But I need to see for chi-sqaured distribution. When I employed the similar formula outer(1:3, 1:3, function(df1, df2) qchisq(0.95, df1, df2)) , I am getting unexpected results. I need to see the following values: p=0.750 ..... 1 1.323

I am trying to understand better an analysis mean RT in various conditions in a within subjects design with the overall mean RT / subject as one of the factors. LME seems to be the right way to do this. using something like m<- lme(rt~ a *b *subjectRT, random= ~1|subject) and then anova(m,type = "marginal"). My understanding is that lme is an easy interface for dummy coding

Dear R users, I have a question about the patterned variance-covariance structure for the random effects in linear mixed effect model. I am reading section 4.2.2 of "Mixed-Effects Models in S and S-Plus" by Jose Pinheiro and Douglas Bates. There is an example of defining a compound symmetry variance-covariance structure for the random effects in a split-plot experiment on varieties of

Dear R users, I am trying to use "muhaz" and "plot.muhaz" functions in "muhaz" package to estimate and plot hazard funciton. However function "muhaz" always gives error message "Error in Surv(times, delta) : object "times" not found". I could not even run their sample codes in the user's manual as follows: data(ovarian)

Hi, I have a dataset which has var1 from 1 sourse and var2 from 2 different methods. I need a new variable such that var2 values from both methods can beused as 1 variable. I believe deming regression can be used to do this. I just don't know how to do it. My data looks like: idvar1var2method1var2method2 11.22.1NA 21.62.4NA 31.52.2NA 41.3NA2.8 51.6NA3.1 61.4NA2.7 Please help. Sincerely,

Dear R-Users, is there any statement to fit a orthogonal regression in R environment? Many thanks in advance. Best regards, Vito Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific learning process." George E. P. Box "Statistical thinking will one day be as necessary for efficient

Hello, I previously sent this message which was stripped off due to HTML mail. Sorry! Thanks. Hello All, I am new to the list. I have been learning to use R recently and its been great to see so much help available. However I must admit, I have stumbled upon a problem with correlation matrices and was hoping if someone could help. I have an excel workbook with a sheet per drug. Each sheet

Hello all; My question is part statistical and part R. I have performed model II major axis regression in R using both the smatr() and lmodel2() packages, but neither offers an option to statistically weight my regression. I have a vector of weights which I would like to apply to each of my regression points (x vs. y), and was hoping that someone out there could provide me with some help on this

Hi, I'm regressing various body dimensions upon body mass using the 'lmodel2' function, as I'm keen to obtain both OLS and RMA slope values. I also wish to create a plot of the regressions, with the 95% confidence interval of both the slope and intercept. I know how to plot 95% ci bands of the OLS slope using lm with the 'predict' function and 'matlines'. Does