search for: diabet

...e functions for each part separately. That isn't an issue necessarily, but i would still like to know why my code won't run. And whether there are any downsides or considerations for using many small functions. Below is my code. I have left part of it out. There are six more parts like the diabetes part that are similar. I also use a lot of data/variabeles not included here, to try and keep things compact. But I can provide additional information if helpful. Thanks it advance for thinking along!! Kind regards, Emily The code: decision_algorithm <- function(AB_list, dataset_ab = data.fr...

Greetings, I checked the Indian diabetes data again and get one tree for the data with reordered columns and another tree for the original data. I compared these two trees, the split points for these two trees are exactly the same but the fitted classes are not the same for some cases. And the misclassification errors are different too....

...60001 80001 101010 healthy2 13333 21231 34111 58761 54086 60002 80002 122222 healthy2 13232 20101 30009 68752 70360 60003 80003 91919 asthma 32132 19889 30733 59959 71783 60237 65603 20374 asthma 34344 20483 31182 70531 59630 40445 56370 98404 asthma 39999 20464 29793 58395 66976 50577 39908 65367 diabetes 10000 20102 29486 51260 68447 42960 50875 216227 diabetes 10111 19143 31275 52573 55459 71337 53090 151505 diabetes 10001 21790 31470 54222 57318 64058 44166 207427 diabetes 15555 20123 30131 59882 71191 46203 44633 197430 acne 12222 31221 51381 64431 55016 43463 60388 74243 acne 12221 30535 4919...

I'm resending this message because I did not include a subject line in my first posting. Apologies for the inconvenience! Tanja > Hello, > > I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when expanding the number of covariates I usually encounter the following error message. > > gm8 <- > glmer(DIAB05F~AGE+as.fact...

Greetings, I am using rpart for classification with "class" method. The test data is the Indian diabetes data from package mlbench. I fitted a classification tree firstly using the original data, and then exchanged the order of Body mass and Plasma glucose which are the strongest/important variables in the growing phase. The second tree is a little different from the first one. The misclassificatio...

Hi everybody! I want to find a closer neighbourins observation. This is my code: ########################## library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F) klasyfikatorKNN=ipredknn(diabetes~glucose+insulin,data=dane,subset=zbior.uczacy,k=3) oceny=predict(klasyfikatorKNN,dane[-zbior.uczacy,],"clas...

Unsubscribe: http://mail4.haemoundheilung.me/unsubscribe.php?M=229682&C=740f45a9d08a410ee15403710005cd65&L=1&N=2 Forget anything you`ve ever been told about Diabetes... Because this `average` man`s discovery has not only CURED over 20.000 people of their diabetes in just two weeks, but it has the potential to wipe out the $245 billion diabetes pharma industry FOR GOOD. And get this - it has NOTHING to do with insulin, exercise, diet or anything else you`ve...

Hi All, I'm hoping someone can help me with a relatively simple problem. Take the following dataset: ID Diabetes ESRD HIV Contact 1 0 0 NA 0 2 1 0 NA 0 3 NA 1 0 0 4 0 NA 0 1 5 1 1 1 0 I want to generate a column called TSTcu...

...ist of patient identifiers and diagnoses from inpatient admissions. I would like to reorganize the list, presently in a long format to a wide format in reshape, but in the absence of a "time" element, I am uncertain how to do this - any help greatly appreciated. ID Dx A nausea A diabetes A kidney failure A heart attack A fever B fever B pneumonia B heart attack B nausea B cough C kidney failure C nausea C foot pain I want this to be ID nausea diabetes kidney_failure heart_attack fever pneumonia A 1 1 1...

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...i, I am trying a linear regression model where the dependent variable is the size of the heart corrected for the patient's height and weight. This is labelled as LAVI. The independent variables are race (european or non-eurpoean), age, sex (male or female) of the patient and whether they have diabetes and high blood pressure. sample size 2000 patients selected from a community. when I model model1<-lm(lavi~age+sex+race+diabetes+hypertension, data=tb1) and model2<-lm(lavi~age+sex+age*race+diabetes+hypertension, data=tb1) in the first model race comes out as a significant predictor (...

Hello, I'm trying to fit a generalized linear mixed model to estimate diabetes prevalence at US county level. To do this I'm using the glmer() function in package lme4. I can fit relatively simple models (i.e. few covariates) but when expanding the number of covariates I usually encounter the following error message. gm8 <- glmer(DIAB05F~AGE+as.factor(SEX)+poolt+poo...

Dear R-Sig-Jobs members, For its Executive Office in Brussels, the International Diabetes Federation (IDF) is looking to hire a Statistician and Data Analyst to join the Policy & Programmes department. This person will be responsible for the management of the high-profile IDF Diabetes Atlas (www.diabetesatlas.org). They will coordinate the collection, analysis, interpretation and...

Dear R-Sig-Jobs members, For its Executive Office in Brussels, The International Diabetes Federation (IDF) is looking to hire a Data Analyst & Coordinator with significant R experience. This person will join the Epidemiology and Public Health unit that sits within the Policy & Programmes department. They will be responsible for the management of IDF?s high-profile Diabetes Atl...

...ld expect the same results from both functions (there might be small differences due to dissimilarity in approximation methods). However, I got a very different results from the two approaches. Here is my R codes and ouputs for the two approaches: 1.) library(geepack)summary(ordgee(UACR~HR+SP+bmi+diabetes+age+HDL+ht.med+male+SCHV+SCRV+smoke+statin+AP,id=x18,mean.link="logit",corstr="independence")) Call: ordgee(formula = UACR ~ HR + SP + bmi + diabetes + age + HDL + ht.med + male + SCHV + SCRV + smoke + statin + AP, id = x18, mean.link = "logit", corstr = "indep...

...one, 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 calculate the weighted prevalence of diabetes and prediabetes in the Year 2011 and 2017 and just subtracted the prevalence of 2011 from the prevalence of 2017 to get the difference in prevalence. But I could not calculate...

Hi I want to create a nice picture about my result of k -the nearest neighbours algorithm. Here is my easy code: ################################# library(klaR) library(ipred) library(mlbench) data(PimaIndiansDiabetes2) dane=na.omit(PimaIndiansDiabetes2)[,c(2,5,9)] dane[,2]=log(dane[,2]) dane[,1:2]=scale(dane[,1:2]) zbior.uczacy=sample(1:nrow(dane),nrow(dane)/2,F) KNN=ipredknn(diabetes~glucose+insulin,data=dane,subset=zbior.uczacy,k=3) KNN=ipredknn(diabetes~glucose+insulin,data=dane,subset=zbior.uczacy,k=3)...

hello I tried to use lars() but neither with my own data nor with the sample data it works. I get in both cases the following error prompt: > data(diabetes) > par(mfrow=c(2,2)) > attach(diabetes) > x<-lars(x,y) Error in one %*% x : requires numeric matrix/vector arguments > x<-lars(x,y, type="lasso") Error in one %*% x : requires numeric matrix/vector arguments > x<-lars(x,y, type="lar") Error in one %*% x...

I am attempting to use the lars package with a sparse input feature matrix, but the following fails: library(Matrix) library(lars) data(diabetes) attach(diabetes) x = as(as.matrix(as.data.frame(x)), 'dgCMatrix') lars(x, y, intercept = FALSE) Error in scale.default(x, FALSE, normx) : > > length of 'scale' must equal the number of columns of 'x' > > More specifically, scale.default fails: normx = new(...

...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 > calculate the weighted prevalence of diabetes and prediabetes in the Year > 2011 and 2017 and just subtracted the prevalence of 2011 from the > prevalence of 2017 to get the difference in prevalence. But I...