search for: ttable

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2013 Feb 04
3
Modifying Package Data
The bio.infer package contains a data frame /usr/lib/R/library/bio.infer/data/itis.ttable.rda that needs to be modified. After loading the bio.infer package and attaching the data frame with the data() function, I wrote the data frame to a text file. After adding another row to the data frame I applied read.table() to create a data frame, but it's in my pwd, not the R library da...
2008 May 24
2
Wine and ALSA
...uot;hw:1,0" rate 48000 channels 8 period_time 0 period_size 1024 buffer_time 0 buffer_size 8192 } } pcm.ch71dup { type route slave.pcm dmix8 slave.channels 8 ttable.0.0 1 ttable.1.1 1 ttable.0.2 1 ttable.1.3 1 ttable.0.4 1 ttable.0.5 1 ttable.0.6 1 ttable.1.7 1 } pcm.duplex { type asym playback.pcm "ch71dup" capture.pcm "hw:1,0" } pcm.!default { type s...
2012 Jun 06
3
Sobel's test for mediation and lme4/nlme
...med, out = out, grpid=grpid) NEWDAT <- na.exclude(NEWDAT) model1 <- lme(out ~ pred, random=~1|grpid,data = NEWDAT) model2 <- lme(out ~ pred + med, random=~1|grpid, data = NEWDAT) model3 <- lme(med ~ pred, random=~1|grpid, data = NEWDAT) mod1.out <- summary(model1)$tTable mod2.out <- summary(model2)$tTable mod3.out <- summary(model3)$tTable indir <- mod3.out[2, 1] * mod2.out[3, 1] effvar <- (mod3.out[2, 1])^2 * (mod2.out[3, 2])^2 + (mod2.out[3, 1])^2 * (mod3.out[2, 2])^2 serr <- sqrt(effvar) zvalue = indir/serr out...
2013 Jan 31
2
rbind Missing Something: Need New Eyes
...chr $ INFRACLASS : chr $ SUPERORDER : chr $ ORDER : chr $ SUBORDER : chr $ INFRAORDER : chr $ SUPERFAMILY: chr $ FAMILY : chr $ SUBFAMILY : chr $ TRIBE : chr $ SUBTRIBE : chr $ GENUS : chr $ TAXON : chr One command (all on one line) is: itis.ttable <- rbind(itis.ttable, data.frame(PHYLUM = "ARTHROPODA", SUBPHYLUM = "MANDIBULATA", SUPERCLASS = NA, CLASS = "INSECTA", SUBCLASS = "DICONDYLIA", INFRACLASS = "PTERYGOTA", SUPERORDER = "PANORPIDA", ORDER = "TRICHOPTERA", SUBORDE...
2012 Jan 21
1
Function for multiple t tests
...iated. I have a working example, as required by the posting guide: my_swiss = swiss[-1,] my_swiss$facto = rep(1:2,nrow(my_swiss)/2) t.test(Fertility~facto,data=my_swiss) by(my_swiss$Fertility,my_swiss$facto, sd) t.test(Agriculture~facto,data=my_swiss) by(my_swiss$Agriculture,my_swiss$facto, sd) ttable <- function(formula, data) { ???? } ttable(Fertility + Agriculture ~ facto, data=my_swiss) facto ? ? ? ? ? ? ?1 ? ? ? ? ? ? ? ? ? ? ? ? ?2 ? ? ? ? ? ? ?Mean ?s.d. ? ? ? ? ? ? ? ? ?Mean s.d. ?t-test p-value Fertility ? ? ?69.19 10.66 ? ? ? ? ? ? ? 70.66 14.38 -0.39 ?0.70 Agriculture ? ?51.65 21...
2006 Apr 10
3
SE estimates for treatment groups from nlme
...model of the following general form: nlme1<-nlme(y~ SasympOrig(x, Asym, lrc), data=df, fixed=list(Asym~A*B*C, lrc~A*B*C), start=c(fixef(ETR.nlme)[1], rep(0,17), fixef(ETR.nlme)[2], rep(0,17))) I am using the default ("contr.treatment" and "contr.poly"). The summary table (tTable) gives me the baseline coefficients and a list of differences and I have no trouble calculating the coefficients for any of my treatment groups by forming the correct linear combination of coefficients. However, I don't understand how to obtain the standard errors for these linear combinations...
2013 Feb 17
2
nested random factor using lme produces errors
...e variable is gut parasites and the factors are moose families which is nested within treatment. My data is balanced. To answer this question, I used the lme function like this : model=lme(parasite~drug,random=~1|drug/family) But doing a summary on this model gives me warning message : In pt(-abs(tTable[, "t-value"]), tTable[, "DF"]) : NaNs produced I don't understand why ?! I noticed that the p-values are not computed and have NAs values for drug2 and drug3 (from the summary of this model) Moreover, in the summary, I noticed that in the random effects line I have standar...
2010 Apr 08
1
formatting a result table (number of digits)
...c <- lme(Ind_Cntrbn ~ D_Clb_Pbl+D_Club+Round+Ind_cntr_1+GR_cntr_1+D_Success_1+IndEarngs_1+D_Unfair_cntr_1+D_1st10rnds+D_Female+D_econ_gov+D_mjr_social+D_frshmn+D_junior+D_senior+UrbanArea+ParentEducation+Empathy+Lcs_Cntrl_Intn+Trust, random=~1|Group, data=Dataset) > s=summary(ic) > t=s$tTable > t Value Std.Error DF t-value p-value (Intercept) 5.683020304 0.78867419 2237 7.20578963 7.853134e-13 D_Clb_Pbl 0.193187682 0.25494452 22 0.75776363 4.566332e-01 D_Club 0.112745107 0.09636280 2237 1.17000650 2.421230e-01 Round...
2007 Jul 30
1
Extract random part of summary nlme
Dear helpers, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value p-value (Intercept) 0.23268607 0.09350662 3990 2.4884449 1.287080e-02 sexM -0.15338225 0.03169762 3990 -4.8389206 1.354802e-06 standLRT 0.38593558 0.016...
2006 Apr 25
1
summary.lme: argument "adjustSigma"
...erting it to a REML-like estimate." Having a look into the code I found: stdFixed <- sqrt(diag(as.matrix(object$varFix))) if (object$method == "ML" && adjustSigma == TRUE) { stdFixed <- sqrt(object$dims$N/(object$dims$N - length(stdFixed))) * stdFixed } tTable <- data.frame(fixed, stdFixed, object$fixDF[["X"]], fixed/stdFixed, fixed) To my understanding, only the standard error for the fixed coefficients is adapted and not the residual standard error. Therefore only the tTable of the output is affected by the argument "adjustSi...
2007 Jul 31
1
Extracting random parameters from summary lme and lmer
LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value p-value (Intercept) 0.23268607 0.09350662 3990 2.4884449 1.287080e-02 sexM -0.15338225 0.03169762 3990 -4.8389206 1.354802e-06 standLRT 0.38593558 0.016...
2010 May 15
1
conditional calculations per row (loop versus apply)
...e Record Type.code Column3 Column4 1 1 0.4 2 3 0.25 3 4 100 4 20 150 5 5 0.4 6 4532 NA I have no problem writing a foor loop to do this for (i in 1:nrow(dataframe) ) { if (Type.code[i]%in%Table.A) Reading[i]<-function 1 else if (Type.code[i]%in%tTable.B) Reading[i]<-function 2 else if (Type.code[i]%in%Table.C) Reading[i]<-function 3 } ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Dr Nick Bond Research Fellow Monash University Victoria, Australia, 38000 Email: Nick.Bond@sci.monash.edu.au ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~...
2006 Jan 10
1
extracting coefficients from lmer
...I could do this if I could extract the coefficients and standard errors from the summaries of the lmer models. This is easy to do for the glmmPQL summaries, using > glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject, data = df, family = binomial), TRUE) > summary(glmmPQL.fit)$tTable Linear mixed-effects model fit by maximum likelihood Data: df AIC BIC logLik 1800.477 1840.391 -890.2384 Random effects: Formula: ~1 | subject (Intercept) Residual StdDev: 0.6355517 0.9650671 Variance function: Structure: fixed weights Formula: ~invwt Fixed effect...
2007 Jul 30
0
Extracting random parameters from summary lme
LS, I'm estimating multilevel regression models, using the lme-function from the nlme-package. Let's say that I estimated a model and stored it inside the object named 'model'. The summary of that model is shown below: Using summary(model)$tTable , I receive the following output: > summary(model)$tTable Value Std.Error DF t-value p-value (Intercept) 0.23268607 0.09350662 3990 2.4884449 1.287080e-02 sexM -0.15338225 0.03169762 3990 -4.8389206 1.354802e-06 standLRT 0.38593558 0.016...
2010 Jun 24
1
Question on WLS (gls vs lm)
...is is not the case. See: library(nlme) f1 <- gls(Petal.Width ~ Species / Petal.Length, data = iris, weights = varIdent(form = ~ 1 | Species)) aa <- attributes(summary(f1)$modelStruct$varStruct)$weights f2 <- lm(Petal.Width ~ Species / Petal.Length, data = iris, weights = aa) summary(f1)$tTable; summary(f2) So, the two models with the very same weights do differ (in terms of standard errors). Could you please explain why? Are these different types of weights? Many thanks in advance, Stats Wolf
2017 Nov 27
0
How to extract coefficients from sequential (type 1) ANOVAs using lmer and lme
...hort.psme.bulk.d13c.3, type ="marginal") ???????????? numDF denDF? F-value p-value (Intercept)????? 1????3 629.4711? 0.0001 narea???? ???????1????2?? 2.7831? 0.2372 sampleheight???? 1????2? 11.6159? 0.0764 > >summary(model.short.psme.bulk.d13c.3, type ="sequential")$tTable ?????????????????? Value? Std.Error DF??t-value????? p-value (Intercept)?? 1.76871397 0.07049685? 3 25.089262 0.0001388446 narea??????? -0.09295561 0.05571991? 2 -1.668266 0.2372012082 sampleheight? 0.13232709 0.03882599? 2?3.408209 0.0763589527 ?(Intercept)??1.76871397 0.07049685? 3 25.089262...
2008 Feb 05
2
How to generate table output of t-test
Hi, Given test <- matrix(c(1, 1,2,2), 2,2) t <- apply(test, 1, t.test) How can I obtain a table of p-values, confidence interval etc, instead of [[1]] One Sample t-test data: newX[, i] t = 3, df = 1, p-value = 0.2048 alternative hypothesis: true mean is not equal to 0 95 percent confidence interval: -4.853102 7.853102 sample estimates: mean of x 1.5 [[2]]
2008 Aug 19
1
R vs Stata on generalized linear mixed models: glmer and xtmelogit
...git' uses 7 points. In order to compare them, I tried also to change the corresponding parameters. This is the code for R: rm(list=ls()) library(faraway); library(lme4); library(MASS) data <- ohio pql <- glmmPQL(resp~smoke+factor(age), random=~1|id, family=binomial,data) summary(pql)$tTable["smoke",1:2] lap <- glmer(resp~smoke+factor(age)+(1|id), family=binomial,data) attributes(summary(lap))$coefs["smoke",1:2] agq7 <- glmer(resp~smoke+factor(age)+(1|id),nAGQ=7,family=binomial,data) write.csv(data,file="data.csv") This is the code for Stata: cle...
2006 Jun 15
1
Repost: Estimation when interaction is present: How do I get get the parameters from nlme?
Gday, This is a repost since I only had one direct reply and I remain mystified- This may be stupidity on my part but it may not be so simple. In brief, my problem is I'm not sure how to extract parameter values/effect sizes from a nonlinear regression model with a significant interaction term. My data sets are dose response curves (force and dose) for muscle that also have two
2003 Jun 25
2
within group variance of the coeficients in LME
Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather