similar to: Estimates for proportions

This question is slightly off topic, but I'll use R to try and make it as relevant as possible. I'm working on a problem where I want to compare estimates from a posterior distribution with a uniform prior with those obtained from a frequentist approach. Under these conditions the estimates should agree. Specifically, I am asking the question, "What is the probability that the true

Dear colleague: Actually that is what is done. When using the z-test between proportions in two different groups, or using chi-squared to test the null hypothesis of equal proportions of two or more groups, the null hypothesis is that H0: p1=p2=p3.....=p where this p is the pooled proportion, the proportion in the summed groups = n1+n2+n3+..../N1+N2+N3.... in the z-test between two

Hello! I want to calculate simultaneous confidence intervals for a nominal variable with three categories: "yes", "no", "partially" and I expect that far more than 5 samples fall into each category. I have read that Glaz & Sison's method is only appropriate for variables with 7 or more categories. Therefore, the Goodman method seems like a good idea. I have

dear list I am student M.S. statistics in department statistics . I am working in the function "nls" in the [R 2.3.1] with 246 data and want to fit the "exp" model to vectors( v and u ) but I have a problem to use it u 5.000000e-13 2.179057e+03 6.537171e+03 1.089529e+04 1.525340e+04 1.961151e+04 2.396963e+04 2.832774e+04 3.268586e+04 3.704397e+04 4.140209e+04

I would like to obtain Confidence Intervals for the estimates (unstandardized beta weights) of each predictor in a WLS regression: m1 = lm(x~ x1+x2+x3, weights=W, data=D) SPSS offers that output by default, and I am not able to find a way to do this in R. I read through predict.lm, but I do not find a way to get the CIs for multiple independent variables. Thank you Torvon [[alternative HTML

Hi - I am using R version 2.13.0. I have run several GLMMs using the glmmPQL function to model the proportion of fish caught in one net to the total caught in both nets by length. I started with a polynomial regression full model with three length terms: l, l^2, and l^3 (l=length). The length terms and intercept were the fixed effects and the random effect was a paired haul (n=18).

I'm simulating a Markov process using a vector of proportions. Each value in the vector represents the proportion of the population who are in a particular state (so the vector sums to 1). I have a square matrix of transition probabilities, and for each tick of the Markov clock the vector is multiplied by the transition matrix. To illustrate the sort of thing I mean: pm <-

Hi all, I have a hypothesis test of proportion question without using R. I hope you could help to answer my question. Here is the statement. ********************* Preliminary data from a feasibility study showed a potential failure level of 1%. A sample size was calculated to detect a potential shift from this 1% level to a 2.5%, at an alpha level of 0.025 and beta of 0.1. The sample size

Dear list, I´m using the mgcv package to model the proportion by weight of certain prey on the stomach content of a predator. This proportion is the ratio of two weights (prey weight over stomach weight), and ranges between 0 and 1. The variance is low when proportion is close to 0 and 1, and higher at intermediate values. It seems that the best way to go is to model this using the

Hi List, I do my best to ask my question in english. ;-) Samba4 integrated heimdal kerberos to do the kerberos work for Active Directory. Some Linux Distributions like fedora/RedHat and openSUSE/SUSE don't accept heimdal even if it is shipped inside samba. Their argument is that heimdal isn't maintained since 2012. Compiling samba against MIT krb5 results in Samba-Packages without

Hi everyone, I've searched the internet and lots of stats books high and low for this one, but nothing seems to be quite what I want. I've got continuous data on four different state activities recorded in seconds, however each continuous session is not equally long, so the data are best expressed as proportions, i.e.: Subject 1: Swimming, 0.5, Hiding, 0.25, Edge, 0.125, Inactive, 0.125

This is partly an R and partly a general statistics question. I'm trying to get confidence intervals of proportions (sometimes for subgroups) estimated from complex survey data. Because a function like prop.test() does not exist for the "survey" package I tried the following: 1) Define a survey object (PSU of clustered sample, population weights); 2) Use svyglm() of the package

Hello Everyone, I was analysing big survey data using survey packages on RStudio. Survey package allows survey data analysis with the design effect.The survey package included functions for all other statistical analysis except two-proportion z tests. I was trying to calculate the difference in prevalence of Diabetes and Prediabetes between the year 2011 and 2017 (with 95%CI). I was able to

Dear Md Kamruzzaman, To answer your second question first, you could just use the svychisq() function. The difference-of-proportion test is equivalent to a chisquare test for the 2-by-2 table. You don't say how you computed the confidence intervals for the two separate proportions, but if you have their standard errors (and if not, you should be able to infer them from the confidence

Hello metafor users, I'm using metafor to perform a single-effect summary estimate of the raw proportion of patients experiencing a post-operative complication, and I'm interested in seeing if this proportion differs between the three most commonly used surgical techniques. The software is working as expected, but I would like to double check on the interpretation of my mixed-effect model

Hello all, If someone could take a little time to help me then I would be very grateful. I studied piping plovers last summer. I watched each chick within a brood for 5 minutes and recorded behaviour, habitat use and foraging rate. There were two Sites, the first with 4 broods and the second with 3 broods. http://r.789695.n4.nabble.com/file/n4511178/Table_PP_Maslo_et_al.png As the data within a

Dear Md Kamruzzaman, I've copied this response to the r-help list, where you originally asked your question. That way, other people can follow the conversation, if they're interested and there will be a record of the solution. Please keep r-help in the loop See below: On 2024-01-17 9:47 p.m., Md. Kamruzzaman wrote: > > Caution: External email. > > > Dear John >

Hello, Does anyone know which method from Newcombe (1998)* is implemented in prop.test for comparing two proportions? I would guess it is the method based on the Wilson score (for single proportion), with and without continuity correction for prop.test(..., correct=FALSE) and prop.test(..., correct=TRUE). These methods would correspond to no. 10 and 11 tested in Newcombe, respectively. Can

Dear list, I have very little experience in dealing with proportions, i am sure this is a very simple question but i could find no suitable answer beyond doing a chi-sq test and then using the Marascuilo procedure as a post-hoc analysis. I am simply wanting to know if the proportions ( i.e the number of Yes / No) significantly differ between the cases and if so which cases are significantly

Hi everyone, I'm using the metafor package to meta-analyze a set of proportions. This is working really well for the raw proportions, but is there a way to back-transform the arcsine transformed proportions in the rma or forest functions with the atransf option? The estimates and CIs for the transformed proportions need to be back-transformed to be the sin of the estimate squared.