similar to: nested (hierarchical) anova

Hi, I wonder if it is possible with the graphics package to overlay one or several plots (barplots, for example) over a map. Data for the map is in a data frame with the latitude and longitude coordinates, and then: > plot(map$long, map$lat, type ="l") produces the map. I want to put each barplot in specific locations on the map, namely at the center of "statistical

Hi I asked a while ago about multiple comparison tests for use with multi--way ANOVAs. Thanks to all those who replied and gave me some ideas and functions. What I ended up doing was writing my own function for Tukey's HSD test (ref: Zar's Biostatistics pg 186-190), as this was the procedure I could best understand. I've included my function here for those who may be interested.

Hi everyone, I'm working with the Epical library, specicatly using the power test in proportions. I think this test is not working like in the book: Biostatistical Analysis (4th Edition): Jerrold H. Zar In the example 23.25. (I attach this Pic) It's not the same answer. Using the follow command don't give the same answer. library(epicalc) power.for.2p(0.75, 0.50, 50, 45, alpha =

Dear list, I would like to plot arrows with different colors according to arrow length, and also (if possible) with head size proportional to arrow length. The idea is to make a quiver-like plot of matlab with wind speed data. So far, I´ve been able to use different colors, but I need to find a more efficient way to recode arrow length intervals into colors. On the contrary, I can't define

Hello all, Here goes one of my first functions. I want to make a nonparametric multiple sample comparison with unequal sample sizes (see Zar?s Biostatistical Analysis, 3rd. Ed., pg. 201 Example 10.11, pg. 288 Example 11.10). In the real world, I want to compare samples of fish length captured with different fishing gears. After using the Kruskal-Wallis test I want to check the differences

Hi everyone, I have a data frame (d), wich has the results of mosquitoes trapping in three different places. I suspect that one of these places (Local=='Palm') is biased by low numbers and will yield slower slopes in the variance-mean regression over the areas. I wonder if these slopes are diferents. I've looked trought the support list for methods for comparing slopes and found the

[This was filtered (looking like spam) and manually approved by your list maintainer, MM ] EvolDir wrote: > Colleagues, > > A few days ago I posted a message inquiring what folks were using for > teaching biostats. I received a stunning 38 replies offering various > opinions, some quite surprising, along with links to web pages, pointers for > coverage, commentaries on

Hello, In doing a series of non-linear estimations of a function which is a sum of a varying number of sinusoids, I would like to "autogenerate" the arguments needed by nls() depending on that number. For example, when there are two sinusoids: > nls( y ~ mu + A1 * cos(2*pi*f1*x - P1) + A2 * cos(2*pi*f2*x - P2), data = some.xy.data, start = list( mu=some.value0,

On 03.12.2013 14:30, Rafael Espíndola wrote: > Can you send a patch? Hi Rafael, the patch is attached. @Mikael, Tim Thanks for the help. I really needed only the link to the repo. Regards, Kai > > On 2 December 2013 06:44, Kai Nacke <kai at redstar.de> wrote: >> Hi! >> >> I like to submit some updates to the LLVM website regarding the LDC >> compiler. All

I've written a g.test() aka log-likelihood ratio test function for my opwn use. It's something I've seen requested (and looked to find myself) on this list a few times. It has the same basic syntax as chisq.test(). It does both goodness of fit tests and tests of independence. Yates' and Williams' corrections are implemented. I've put some examples from Sokal & Rohlf

Hi everybody, Excuse me for this silly question, but after searching the help archives I'm still unable to find my way to read the source code of the "biplot" function in R. I have installed the mvbutils package, and tried: > fixr(biplot) which only gives me: function (x, ...) UseMethod("biplot") with no further details.... I'd like to read the code to see if

Same here. I called them yesterday plus email and still no reply. -----Original Message----- From: asterisk-users-bounces@lists.digium.com [mailto:asterisk-users-bounces@lists.digium.com] On Behalf Of brett-asterisk@worldcall.net Sent: Friday, January 21, 2005 10:28 AM To: Asterisk Users Mailing List - Non-Commercial Discussion Subject: Re: [Asterisk-Users] Webmin Module for Asterisk (and

I'm testing out quantstrat using a simple one-indicator strategy. The error I get after applyStrategy(...) is Error in .xts(e, .index(e1), .indexCLASS = indexClass(e1), .indexFORMAT = indexFormat(e1), : index length must match number of observations In addition: Warning messages: 1: In match.names(column, colnames(data)) : all columns not located in roc_15 for STOXX.Open STOXX.High

Hi, I'm sure this one is very easy.... I am trying to write a function where one of its arguments has two posible (strings) values, defaulting to one of them if none is specified. My problem is that when evaluating the function the following warning is produced: "the condition has length > 1 and only the first element will be used" I've read the help page of if() but I

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I am trying to do a Nonparametric Tukey-type multiple comparison post-hoc test to determine which groups are significantly different. I have read the dialogue on this topic from the R-help, and am still not clear why no statistical packages include this test as an option? Is it not an appropriate test to conduct on non-normally distributed data? Is the only option to calculate it by hand

Hi, I'm newbie in R package, but i'm extremely gratefull for these list! is there possible to make kruskal.test summarize the sum of ranks?? e.g ##### z<-c(1.2,3.4,0,0,0,0,0) ranks(z) # like in octave package ans= 6 7 3 3 3 3 3 sum(ranks(z)) ans= 28 ### then apply multiple comparisions for many other data SE<-sqrt(n*(n*k)*(n*k+1)/12) # according Zar,JH. Bioestatistical

I need to specify error terms properly in a mixed-effects anova model. I know you can add error terms in aov using Error and can specify random factors in lme but I am not sure how these get treated. When making the calculations for fixed and random factors, are the correct error terms used and how can you get aov or lme to use different error terms for fixed and random effects? I'm

How I make the below matrix | a^0 0 0 ... 0 | | a^1 a^0 0 ... 0 | | a^2 a^1 a^0 ... 0 | | . | | . | | . | | a^n a^(n-1) a^(n-2) ... a^0 | with no loops, where "a" is a constant? ======================================================================== C?zar de Freitas Depto. de Estat?stica - UFPE Recife - Pernambuco - Brasil

Hi community, Seems I am too stupid: I try to calculate with power.t.test() an example from the statistics textbook [Jerrold H. Zar, Biostatistical Analysis, 2nd edition, Prentice Hall, 1984, Chapter 8, Exercise 8.4, (page 120)]: ------- A sample of size 18 has a mean of 13.55cm and a variance of 6.4512cm^2. (a) Calculate the 95% confidence interval for the population mean. (b) How large a