similar to: nested cross-sectional design using lmer or nlme

Howdy What I 'd like to analyze with a large data on building permits is to find time series effect of urban policy on buildings as well as cross-sectional effects in any. In 1990 the specialZone urban policy was introduced. I guess that the effects of this specialZone policy would be different from countys. There are counties that do not welcome this specialZone forced to design it. One of

I have one fixed effect, sor, with two levels. I have eight lots and three wafers from each lot. I have included the data below. I would like to fit a mixed model that estimates a covariance parameter for wafer, which is nested in lot, and two covariance parameters for lot, one for each level of sor. The following command fits the model that I want, except for it estimates the correlation

Dear all, I'm investigating on how to estimate a specific kind of cross- classified multilevel model. I think it is often referred to as a multiple-membership model. To problem is this: I want to study changing attitudes of people, for which I use (amongst other things) contextual data of the neighborhood they live in. I have two surveys (panel-design) and I know the neighborhood

Hola a todos, mi consulta va relacionada con los paquete nlme o lmer. Mi idea va relacionada a correr un modelo lineal mixto en el cual una de las matrices de incidencia (Z), sea previamente formada por la suma de dos matrices o por su puperposición (Z1+Z2=Z) dentro de esas funciones. Con un ejemplo creo que me explicaré mejor outputF<-lmer(formula=ALT~ (1|MADRE)+(1|PADRE)+(1|FAMILIA),

Dear Dennis, Your question assumes that people know both SAS PROC MIXED and R nlme. Only a limited number of people do. Add the mathematical formulation of the model. That will increase the number of people that can help you. Adding the number of levels in each categorical variable and the number of observation per group is useful too. Best regards, ir. Thierry Onkelinx Instituut voor natuur-

Dear R users: I have some difficulties analizing data with mixed effects NLME and the last version of R. More concretely, I have a repeated measures design with a single group and 2 experimental factors (say A and B) and my interest is to compare additive and nonadditive models. suj rv A B 1 s1 4 a1 b1 2 s1 5 a1 b2 3 s1 7 a1 b3 4 s1 1 a2

I am trying to reproduce some old SAS PROC MIXED code using R and nlme. The data consists of emission readings from vehicles and fuel properties. All variables are real numbers except "study" and "vehicle", which are character. Unfortunately, since the data are confidential, I'm unable to provide an example. The original SAS v6.12 code is provided below:

Hi, I have a dataset from ILO, originally in csv-format, that I have read into R. It is cross-sectional time-series data, so I have a bunch of variables and dummy variables that I need to extract data from for the entire time period. However, the years are separated by columns instead of rows, as is usually the case in R. This is what it looks like: > str(laborstafinMFBA)

This is probably very simple but my brain has frozen over. (I'm trying to warm it with coffee) I have observations of around 22000 individuals over 13 successive years: they were either 'interviewed' at time t or 'not interviewed'. What's the most appropriate function/approach to use to find out the extent to which individuals' event outcomes are temporally

Phelps, Matthew wrote: > On Thu, Feb 28, 2019 at 11:52 AM mark <m.roth at 5-cent.us> wrote: >> Nicolas Kovacs wrote: >>> Le 28/02/2019 ? 04:12, Jobst Schmalenbach a ?crit : >>>> I want to lock in the SDA/SDB/SDC for my drives >>> >>> In short : use UUIDs or labels instead of hardcoding /dev/sdX. >>> >>>

Hello, I have been using the TM package to create a TermDocMatrix, which I have saved as a matrix so that I can view word frequencies. Below is a section of the code that I have used and an excerpt of the output: What I wanted to be able to do is to view the output alphabetically - rather than the results being sorted by frequency as below, that an alphabetical list would be generated. This

Hello, supposing that I have two or three clear categories for my data, lets say pet preferece across fish, cat, dog. Lets say most people rate their preference as being mostly one of the categories. I want to do pca on the data to see three 'groups' of people, one group for fish, one for cat and one for dog. I would like to see the odd person who likes both or all three in the

Hello, all, I am running some simulations to estimate power for a complicated epidemiological study, and am using lme and lmer to get these estimates. I have to run a few thousand iterations, and once in a great while, an iteration will create fake data such that the model won't converge. I see from Google searches that this is not an uncommon situation. My question: is there a way to

Dear R List, I am trying to use mixed models to analyze an intervention and want to make sure I am doing it correctly. The intervention is for lowing cholesterol and there are two groups: one with an intervention and one without. The subjects were evaluated a differing amount of time, so there were between 2 and 7 visits, equally spaced. Sample output is below. TC is total cholesterol,

Dear R saviors, kindly address to this problem, I would really appreciate any takers. I am trying to resolve this issue of IMR in clustered (multilevel) cross-sectional panel data for more than two months now,. The characteristics of my dataset are as follows: - some 900 000 individuals - total of 60 countries - cross-sectional time series at the country level max 10 years, not all

Hi R-users!! I have some trouble with the survey pakage and i would be very glad if you can give me an advice. I have a sample from a survey where household were interviewed. The sample has 4 criteria on which the stratification was based: REGION, SIZE OF HOUSEHOLD, SIZE OF LOCALITY, AGE OF HEAD OF HOUSEHOLD. Since i don't have the whole information in each cell of the cross

Hi all, Is there a package in R to perform time series cross-sectional regression analysis (like the TSCSREG procedure in SAS)? Thanks for the info. Thanks and Regards, Shubha Karanth | Amba Research Ph +91 80 3980 8283 | Mob +91 94 4886 4510 Bangalore * Colombo * London * New York * San José * Singapore * www.ambaresearch.com This e-mail may contain confidential and/or

Hello all! When you are working with a little more complicated models in SAS PROC MIXED, you often use the /ddfm=satterth call to make sure the df decomposition is done the best way possible. Running the same models in lme, without any special calls, results in warning messages about the df handling. Is anybody out there working with something like the /ddfm=satterth? It would be handy, or

Hello, I am new to R. I would like others to explain to me how to add absolute values inside the individual stacked bars in a consistent way using the basic R plotting function (R base). I tried to plot a stacked bar graph using R base but the values appear in an inconsistent/illogical way in such a way that its supposed to be 100% for each village but they don't sum up to 100%. Here is the

I think it is easiest to describe what I want in terms of the concrete problem I have. I have data from a number of countries in each of which a sample of people was interviewed. In presenting the results in a forthcoming collaborative publication much emphasis will be placed on the multi-centre nature of the study. Although I suspect colleagues may do this with shaded maps I would prefer to