In this case education deciles term appears to be a continuous. If it has a minimum of 0 then all estimates are referenced off that 0 value. Predictions of whatever effect is under consideration ...

Engineering failure-time analysis is very similar to demographic analysis of human survival. In both cases there is typically an early failure rate (infant mortality) and an aging process. In ...

You are dealing with count data, so technically the MW test (equivalently Wilcoxon rank sum), which deals with continuous outcomes, would not be the theoretically "correct" method. There are ...

Frank's answer mentions stratification, and that was the route I was pursuing when I suggested you move your earlier closed question to CV.com. As I suggested in a comment you did get an answer from a ...

There wouldn't be any uncertainty for the mass but the same errors in position would seem to exist for the position of the starting point as exist for the displaced locations of the spring end-point ...

Generally an R regression 'control' list defaults to the first item in the parameter character vector (which looking at the Usage section of the help page is "inbag"). So if you did offer a &...

The collinearity is not between those two variables. They both have coefficients. Rather it is a joint collinearity between the two variables and the interaction variable. The interaction variable is ...

P-values are a measure of the strength of evidence against a particular null hypothesis. You have specified that the null hypothesis is that the trend is either zero or decreasing posed against the ...

The specific answer to the question is "yes, that is a linear model". In R the "*" operator used in a formula creates what is known as an interaction. If those two variables are ...

It means you have many test cases, or that you are using software that does smoothing. It also means you have a test result that is continuous rather than categorical.

The way to get times for particular probabilities rather than probability for particular time you need the inverse of the survival function which is the quantile function. The flexsurv package also ...

Reprex (courtesy of https://easystats.github.io/blog/posts/performance_check_collinearity/): library(glmmTMB); library(performance) #note: needed to also install the insight package before ...

You might start thinking about the simple case of a "binomial experiment". If you have a fair coin and flip it 11 times, the probability of getting 11 heads in a row would be: 0.5^11 # 0....

In general it is unproductive to attempt interpretation of individual coefficients. It is more direct to create predictions along the range of values for the continuous variables with specific values ...

Complete linear dependency between two variables is very simple to test: if( cor(v1,v2) != 1 ) { print("v1 is not linearly dependent on v2"} It's extremely unlikely that a factor variable and a ...

Klein and Moeschberger's text "Survival Analysis" (p 195-197) has a nice comparison of these tests and a few others. They differ in the weighting of events along the course of the study: The Gehan ...

What you can do will depend strongly on the numbers of events in the 0-3, 3-6, and 6+ month groups. If you have adequate numbers, say from a Medicare study of discharged patients, you could simply ...

Typically in that situation you might construct a case within cohort analysis and use the non-cases as the controls analyzed from T0 to T1. I suppose you could set the study with a 4-1 match of ...

The question authors were clearly trying to get you to compare pre-post differences across groups. In that framework where mu was the mean of the group differences, the hypothesis would be that mu[A] =...

The default coding of factor variables in R is "treatment contrasts" relative to the first level in the factor definition. There are many other possible contrast arrangements possible. This is not ...

When I read this question:"Does frequency of occurrence (FO) of pieces eaten differ between species or year?", I do not immediately think of using a 2-factor interaction model, but rather will have ...

I think you might make progress by asking your audience to assume that these values are distributed on the range [0,5] in the set {(0:10)/2} with a beta-binomial distribution. The beta-binomial ...

Confidence intervals answer the question: "What is the range of plausible findings under the triparte assumption that the population is Normally distributed, the mean is the observed value and the ...

I'm not sure that we are reading the data situation similarly. As I understand it ... all of these patients have had at least one diagnosed episode of bladder cancer. The coxph-model you created with ...

The formula interface for regression functions in R would allow you to automatically generate n-way interactions very simply. Unfortunately this results in a combinatoric explosion. You could take ...

The default type of spline with splinefun is "fmm" and the help page says: If method = "fmm", the spline used is that of Forsythe, Malcolm and Moler (an exact cubic is fitted through the four ...

A chi-square statistic is the sum of the squared deviations for some expected pattern. If there are minimal deviations, then the chi-squared is small and the p-value is "chance-like", i.e. it's not ...

There is at least one discrete variable, parm3 and it's possible that there are other un-labeled groupings. I'd start by redo that graphic while labeling the parm3 values with color coding. Ten you ...