DWin
  • Member for 11 years, 2 months
  • Last seen this week
  • Alameda, CA
Explanation of the Markov chain in the given plot
1 votes

It is assuming that sibs will be mating. Looking at that transition matrix you can see that both the S1 and S6 states will be "absorbing, i.e. once the historical situation results in either of those ...

View answer
Algorithm to cluster chart type
1 votes

Your request made me wonder if the functional data analysis framework might be helpful. In R it is implemented in the tools within several packages, all with the letters "fda" in their titles. A ...

View answer
Compare KM curve to Cox Proportional Hazard model with multiple variables
1 votes

(I don't understand why you didn't pose the question using one of the available datasets in the 'survival' package.) Generally you can get a no-covariate models with code like: newm3<-coxph(Surv(...

View answer
Level of factor taken as intercept?
Accepted answer
1 votes

That's how "treatment contrasts" work. One column of the model matrix is taken by the "first" factor in that simple model. Each statistical system chooses a default contrast strategy, so R's is ...

View answer
Which Model is better in R?
1 votes

Model 2 is more parsimonious and the R^2 is insignificantly smaller than the first model. The adjusted R^2 takes into account the fact that fewer degrees of freedom are needed to get to this level of ...

View answer
Logistic regression "1 not defined because of singularities"
1 votes

If you have no patients in the cross-tabulated CT:AA cell it really begs for an answer to "why". Is it just a sampling anomaly, or is it telling you something about the biology of these two genotypes? ...

View answer
Interpreting Coefficients of a Linear Model
1 votes

Coefficients RoadCem and RoadMud will differ from RoadCon at Day==0 by -3.633496e-01 and 7.555775e-01 respectively. The Days coefficient, -5.365565e-06, is the amount by which index will decrease ...

View answer
Simple cross-tabulated data and probability
Accepted answer
1 votes

Independent estimates of proportions (which is what the coin toss is achieving) means you cannot improve or even modify the conditional probability in students beyond what is provided by the ...

View answer
Logistic Regression as an adjunct to Survival Analysis
1 votes

The situation you describe might be handled well with either Poisson regression or with Cox PH regression. (Although there are some hints in your question that the constant hazards and/or the ...

View answer
Probability of being $\$5$ up after $25$ plays of a game of Heads and Tails (fair coin)
Accepted answer
1 votes

Antoni's answer is better than mine since it has a deeper mathematical underpinning but mine is quicker. Using R the answer comes immediately from looking at the the number of "wins" needed to be "5 ...

View answer
Appropriate priors for truncated regression model
1 votes

If you need to limit the responses to positive values, you can construct a "tobit" model with the survreg function in Therneau's survival package for R. There is a worked example in the help page for ?...

View answer
Comparing a linear model with a spline model
1 votes

The "p-value" could be called an "unlikelihood statistics". It is supposed to be the extent to which the data disagrees with the Null or "alternative model". TYu are actually performing a "likelihood ...

View answer
Survival analysis with cures when it is known that for some subjects the event (death) will never occur
1 votes

If you can establish that they are "cured", then they are no longer in the risk set for dying of the condition under treatment. Estimating hazards requires that you divide the events by the number at ...

View answer
Competing hazards for event that makes the event of interest more likely
1 votes

I think you might look for modeling frameworks where clients are in a few different states (perhaps: new user, established-user, established-new-problem, frustrated-user) and use survival analysis to ...

View answer
Survival analysis / cox-regression of periodically recurring events
Accepted answer
1 votes

Looks like you have a predictor that varies cyclically. My impression from very limited reading of the botanical literature is that something along the lines of cumsum(degree_days) (where the sums are ...

View answer
Hazard estimate of 'muhaz' function?
Accepted answer
1 votes

When you censor by simply choosing to randomly change the censoring variable, you are essentially leaving in all of the case-"times" under observation until just before they would have died during a ...

View answer
What is my lambda here
1 votes

The exponential distribution has a mean that is somewhat "before" the 50%-tile of its associated survival curve. Because of the memoryless property, the probability of survival to 12 years is exactly ...

View answer
Cox Regression: Testing for effect in subgroup
1 votes

As far as R programming goes, the formula you offer is equivalent to: s ~ age * treatment The asterisk-operator is overloaded in R. When its arguments are numeric, it is multiplication, and when ...

View answer
Interpreting Cox & Binomial Regression: non-significant Chi-Square values w/ significant wald statistics
Accepted answer
1 votes

Scenario1: Neither of your proposed assessments of significance would be considered optimal for assessing the contributions of specific variables. You should look at the change in deviance (which is -...

View answer
Comparison method for curves using percentiles
1 votes

This is the code I would have used to do what I thought you were describing: > aggregate(modvar ~ var_cut, df, function(x) quantile(x, c(0.05, 0.95))) var_cut modvar.5% modvar.95% 1 1 1....

View answer
Goodness of fit – Testing Cox proportional hazard assumption in R
1 votes

The cox.zph function is measuring the overall effects of relaxing the assumption that the effect is constant in time. It telling you that the effect is probably not constant, but it's not telling you ...

View answer
Difference between restricted and unrestricted parameter space in MLE
1 votes

If you read the available theory referenced in the help page, you see that the authors are building a likelihood for a mixture model and considering a dividing line (in the case of two component ...

View answer
What is the proper way to do vector based linear regression in R
1 votes

I suggest that your question is somewhat statistically naive in not actually describing the uses to which this operation might be employed. Matrix outcomes can be of various sorts. You ask for "...

View answer
Is there any repository with interval censored time-to-event datasets?
1 votes

I'm not aware of any repository but there are R (open source) packages, including the recommended survival package that have such datasets associated with worked examples. Doing a Google search with: "...

View answer
For the survival analysis package in R, what is the log-likelihood of "survreg( Surv(time, censor) ~ age, dist="exponential")"?
1 votes

I think it would be more accurate to say that: $l(\theta) = \sum( \log(\theta) )- \sum( \theta Y_i)$ $l(\theta) = n_u \log(\theta) )- \sum( \theta Y_i)$ where u's are uncensored and Y's are ...

View answer
How does Cox proportional hazards model deal with time-dependent variables?
1 votes

Within categories of the covariates there will be a calculation of the cumulative hazard as a function of the time from beginning of the observations, summing intervals until either an event or a ...

View answer
Regression of proportions
1 votes

Your analysis would be improved if you had populations for each of the districts. The variance of the rates will depend on the counts, so the standard deviation of each of the rates will be ...

View answer
How to calculate percent deviance explained on square-root-transformed dependent variable?
1 votes

The % deviance explained is calculated by comparing the predictions (fit$fitted.values in R) for Y to actual values of Y. It does not take into account any transformations on the explanatory ...

View answer
What is the best method of performing a chi-squared test with only one set of data?
1 votes

The basic chi-square statistic for a test of a proportion being from a population with an expected of 19.8 is (O-E)^2/E = 6.52. (We do need to ask you here whether that was a numeric expected of 19....

View answer
Python + R: How much R do I need to know to use random R libraries in python Using Rpy2
Accepted answer
1 votes

You will need to know the differences between dataframes, matrices and lists. Also the differences between the R vector data types (logical, character, numeric, factor, list) and language types (...

View answer
1
3 4
5
6 7