similar to: Outliers in Binary Logistic Regressions

Hallo there, greetings from Germany. I have a simple question for you. I have run a binary logistic model, but there are lots of outliers distorting the real results. I have tried to get rid of the outliers using the following commands: remove = -c(56, 303, 365, 391, 512, 746, 859, 940, 1037, 1042, 1138, 1355) MIGRATION.rebuild <- glm(MIGRATION, subset=remove)

Dear R-users, Following is part of my data, where slide has 36 levels and block 48 levels. I have done boxplot for each slide on the same graph. There are outliers for each slide and I tried to use indentify functtion to identify outliers in such a way that when I click on an outlier or point, the points will be labelled by either their block or ID or by both but without success. How can I make

Hallo there, can anymore show me how to get results about konkordant und diskordant paars (Sommer-D, Gudman-Krustal-Gama, Kendall-Tau-a) within a logistic regression) in R? Thanks a lot. MT [[alternative HTML version deleted]]

Hallo there, I've got a simple question concerning a plot attempt of mine. I am trying to plot two variables using the following code: # Creating a Graph attach(Jitirana) plot(Sozialkapital, Migration) abline(lm(Migration~Sozialkapital)) title("Regression of Sozialkapital on Migration") Simple thing, but the problem lies in the fact that I keep receiving a square plot depicting y on

Hi Friends I am new here and have a problem Year Market Winner BID 1 1990 ABC Apple 0.1260 2 1990 ABC Apple 0.1395 3 1990 EFG Pear 0.1350 4 1991 EFG Apple 0.1113 5 1991 EFG Orange 0.1094 For each year and separately for the two

Dear Helpers, I just started working with R and I'm a bit overloaded with information. My data is from marsupials reindroduced in a area. I have weight(wt), hind foot lenghts(pes) as continues variables and origin and gender as categorial. condition is just the residuals i took from the model. > names(dat1) [1] "wt" "pes" "origin" "gender"

dear all, could somebody tell me how I can plot mild outliers as a circle(?) and extreme outliers as an asterisk(*) in a box-whisker plot? Thanks very much in advance -- View this message in context: http://www.nabble.com/mild-and-extreme-outliers-in-boxplot-tp25040545p25040545.html Sent from the R help mailing list archive at Nabble.com.

Happy holidays all! I know it's very subjective to determine whether some data is outlier or not... But are there reasonally good and realistic methods of identifying outliers in R? Thanks a lot! [[alternative HTML version deleted]]

Hi All, I am working on the dataset in which some of the variables have more than one observations with outliers . I am using below mentioned sample script library(outliers) x1 <- c(10, 10, 11, 12, 13, 14, 14, 10, 11, 13, 12, 13, 10, 19, 18, 17, 10099, 10099, 10098) outlier_tf1 = outlier(x1,logical=TRUE) find_outlier1 = which(outlier_tf1==TRUE, arr.ind=TRUE) beh_input_ro1 =

Hi, I have been using the lqs function with method='lms'. However the results I get are a little different from the results noted by Rousseeuw & Leroy (Robust Regression and Outlier Detection) and I was wondering how to use these results for outlier detection. I'm using the stackloss dataset, for which the original Rousseeuw et al. program points out that observations 1,2,3,4

Hello all, I have a question: I am using the interquantile method to spot outliers & it gives me values of say 234 & -120 or for the higher & lower benchmarks. I don't have any issues w/ the higher end. However I don't have any negative values. My lowest possible value is 0. Should I consider 0 as an outlier? Thanks ahead for your thoughts -- View this message in

Dear R-helpers, Very small amount of outliers can greatly affect the mean and many other statistic of a numeric variable. So, usually we must deal with the outliers properly in the process of data analysis. Here, I want to replace outliers with the group median of the variable. But, I can not construct a good way to do that efficiently, because of I am a newbie to R and programming. Can anybody

Hi everybody, I'd like to know if there's an easy way for extracting outliers record from a dataset, in order to perform further analysis on them. Thanks Alessandro

Hi, I am a new user of R. This is a conceptual doubt regarding screeing out outliers from the dataset in regression. I read up that Cook's distance can be used and if we want to remove influential observations, we can use the metric (>4/n) (n=no of observations) to remove any outliers. I also came across Grubb's test to identify outliers in univariate distns. (assumed normal) but i

Hi Experts, I am new to R, using following sample code for capping outliers using percentile information. Working on large data (30000 observations and 150 variables), loop I am using in the below mentioned code for detecting outliers and capping to upper /lower percentile value is taking much time for the execution. Is there anything wrong with code, can anyone suggest improvement in the script

I am having trouble plotting outliers on time series. Give then following code: ############################################################ # find STL Outliers by weight and append sh2, use Robust # this should allow the initial outliers to be filtered # this section may be commented out. ############################################################ tsSourceDiag <-

Suppose I am reading data from a file and the data contains some outliers. I want to know if it is possible in R to automatically detect outliers in a dataset and remove them -- View this message in context: http://n4.nabble.com/How-to-detect-and-exclude-outliers-in-R-tp1017285p1017285.html Sent from the R help mailing list archive at Nabble.com.

Hi, I am new to R and I would like to get your help in finding 'outliers'. I have mvoutlier package installed in my system and added the package . But I not able find a function from 'mvoutlier' package which will identify 'outliers'. This is the sample list of data I have got which has one out-lier. 11489 11008 11873 80000000 9558 8645 8024 8371 It will

Dear R-users, I have two outliers related questions. I. I have a vector consisting of 69 values. mean = 0.00086 SD = 0.02152 The shape of EDA graphics (boxplots, density plots) is heavily distorted due to outliers. How to define the interval for outliers exception? Is <2SD - mean + 2SD> interval a correct approach? Or should I define 95% (or 99%) limit of agreement for data interval,

Hi All- I have 24 boxplots on one graph. I do not have the whiskers extending to the outliers, but I would like to label the maximum value of each outlier above the whiskers. I have the stats but am having trouble figuring out how to label the whiskers. Any suggestions would be great! sherri