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Questions related from Jochen Wilhelm
Given there is some k-step (k=3 or 5 or 7 etc) Likert data with "absolutely no" on one side, "absolutely yes" on the other side, and "neutral" in the middle. A correct way to analyze such...
08 August 2020 1,242 5 View
Using RStudio and rMarkdown, I have an ioslides presentation (an html file). On one of the slides I want to have a link (cross-ref) to another slide in the same html. I did not find any useful...
29 May 2020 2,918 0 View
It's a weighted least-squares polynomial regression, so it's based on assuming normal errors, and the normal probability model is parametric. However, in some statistics book and online statistics...
29 October 2018 3,128 6 View
I have two models to predict "Survival" (S in (0;1)) from a "Dose" (D, D≥0): a 2-parameter Weibull model:S(D) = exp( -exp(a*logD-b) ) and a so-called "multi-target model":S(D) = 1 - ( 1-exp(-D/t)...
28 January 2016 558 7 View
Consider following case: There are k different groups, but only the mean difference between 2 of these groups should be tested (t-test, consider the assumptions are met and alpha and beta are...
15 October 2015 8,067 11 View
On a given microarray design there are multiple different probes spotted for many genes. The (normalized) signals of the features (all referring to the same gene) often are quite different (log2...
05 March 2015 8,797 5 View
Short history: As I understood can the normalized (profile) likelihood be used to get the CI of an estimate. "Normalized" means that the function will have a unit integral. This works beautifully...
06 December 2014 8,905 5 View
I'd like to have or write a function that automatically provides "adjusted predictions" for a linear model. For simplicity I could accept that the models must not have any interactions. With...
12 July 2014 2,558 4 View
A parameter of a statistical model should be estimated from iid data. For simplicity, let's consider a single-parameter model. The likelihood principle sais that the best estimate for the...
19 March 2014 4,842 56 View
I want to plot data for a two-factorial experiment in a simple boxplot. The attached diagram shows an example. The grouping structure of the second factor should be indicated by horizontal lines...
13 February 2014 1,021 8 View
I tried to find out why the deviance in GLMs is defined as -2*log(LR) (with LR being the likelihood ratio). Why the factor -2? Often, authors state that this way the deviance for a normal model...
29 April 2013 1,943 3 View
Background: From a binomial experiment (k successes in n trials), the proportion of successes in the "population" is estimated by p = k/n. This estimate has a standard error of SE =...
15 February 2013 3,871 9 View
I am not familiar with the grid package. I usually use "plot" (graphics) to show data and set the arguments xlim and ylim to define the visible parts of the x- and y-axes. I would like to this for...
30 November 2012 9,580 7 View
In many texts I find the statement that the likelihood is a normal-Gamma, e.g. here: http://www.cs.ubc.ca/~murphyk/Papers/bayesGauss.pdf (3.1, 3.2). I never found anything explaining HOW this is...
24 October 2012 1,561 43 View
There is a couple of error models (probability distributions) where I do understand the derivation in terms of going from simple processes where you have limited knowledge (uncertainty) to the...
19 September 2012 9,835 10 View
I know that Euler solved this somehow for a=1 and came to the value of e. I also found a series expansion that Euler developed. However, is there someone who could explain the derivation ending up...
14 September 2012 2,042 3 View
Does anyone know sources/references with derivations of the normal distribution, at best ones with explanations that can be understood by people without mathematical background? I am aware of the...
13 September 2012 3,715 3 View
I am looking for an example to determine the coefficients of a GLM by maximizing the (log)likelihood, preferrably using R. The optimization (search algorithm) is not the problem; this can be done...
10 September 2012 3,377 6 View
It's well known that proportions (real valued data in [0,1]) can be modelled using beta regression models. If the values are in other intervals with known limits, one can always scale the data...
01 January 1970 6,696 18 View
