DWin
  • Member for 11 years, 2 months
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  • Alameda, CA
Poisson Regression with both categorical and numerical variables: interpreting the outcomes and intercept
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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 ...

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Predicting failures of a part using historical failure data
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1 votes

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 ...

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Is Mann Whitney U the right statistical test for this analysis?
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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 ...

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Correcting for a covariate in a Kaplan-Meier curve
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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 ...

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adding point (0,0) to data set and its uncertainty?
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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 ...

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R: What is meant by "inbag" risk and "oobag" risk in mboost?
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1 votes

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 &...

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Collinearity in dataset, but I don't know why
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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 ...

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Understanding Cochran-Armitage Trend Test in R
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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 ...

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What does linear stand for in linear regression?
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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 ...

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What does it mean if ROC curves (training ROCs) are very smooth?
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3 votes

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.

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Formula for predicting median survival using a Royston-Parmar model
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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 ...

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How to test multicollinearity in Fixed Effects Model in R?
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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 ...

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A way to estimate whether a coin is biased based on the run of heads/tails parameter?
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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 #[1] 0....

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Interpretation of Coefficients using spline ns() in glm
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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 ...

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linear regression with variables which are possibly dependent to each other
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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 ...

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Difference in log-rank, tarone-ware, gehan-breslow, Peto-Peto etc
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1 votes

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 ...

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Appropriate statistical analysis for predicting early death or early progression
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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 ...

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Nested case-control and Cox proportional analysis
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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 ...

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Statistical model & hypothesis test
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2 votes

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] =...

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Dummy Variables vs Factor Usage in R for building Cox Regression
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2 votes

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 ...

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p-values near 1.000 for all tests in a glm() (count and binary data, Poisson and binomial distributions)
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1 votes

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 ...

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Confidence interval for beta-binomial distribution with restricted range
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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 ...

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95% Confidence Intervals
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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 ...

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Interpret survival curve for multiple-event Cox proportional hazard model
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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 ...

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How to choose the best combination of covariates in Cox multiple regression?
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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 ...

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splinefun build in function in R-programming
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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 ...

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Meaning of chi-squared in R Kruskal-Wallis test
3 votes

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 ...

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Do "splits" in scatterplots indicate anything?
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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 ...

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Should I use an independent sample t-test or a Mann-Whitney test?
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To start ... you really are not giving us enough information to give well-considered opinions. The t-test is reasonably robust to some departures from normality. The key questions are whether there ...

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data analysis for a partial two-by-two factorial design
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You would not be able to assess the effect on "response" from drug A alone but you would be able to assess the incremental effect of drug A+drug B (versus no drug) when compared to drug B alone (...

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