# All Questions

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### Methods of fitting a dynamic linear model

I'm taking a time series course and am learning about exchangeable time series form of dynamic linear models (DLMs). This is given by: \begin{align*} \mathbf{y}_t' &= ...
18 views

### What is the best way to remember the difference between sensitivity, specificity, precision, accuracy, and recall?

Despite having seen these terms 502847894789 times, I cannot for the life of me remember the difference between sensitivity, specificity, precision, accuracy, and recall. They're pretty simple ...
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### Is there any use of having dual error bars in bar charts to show both descriptive and inferential statistics?

I would like to display information both about the distribution of the population and the certainty in the measurements in the same plot. Would there be any use of having dual error bars in a barchart ...
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### Do the estimated values from a Best Linear Unbiased Predictor (BLUP) differ from a Best Linear Unbiased Estimator (BLUE)? And if so, why?

I understand that the difference between the is related to whether the grouping variable in the model is estimated as a fixed or random effect, but it's not clear to me why they are not the same (if ...
4 views

### Confidence interval on replicates from multinomial distribution with bimodal outcomes

I have a Java model which tracks the numbers of 6 types (A-F) of individuals. I am interested in the distribution of different types of individual across simulations with different parameter values. ...
14 views

### Latent Class Analysis vs. Cluster Analysis - differences in inferences?

What are the differences in inferences that can be made from a latent class analysis (LCA) versus a cluster analysis? Is it correct that a LCA assumes an underlying latent variable that gives rise to ...
13 views

### Logistic Regression using fractional polynomials in R

I have been developing a model based on trauma data of head injury in the UK. The key outcome is 30 day mortality (denoted as "Survival" measure). In a dataset of 2134 patients, there are other ...
9 views

### Cointegration - Why can't I estimate a VAR on the differences?

When talking about variables that are I(1) (the first difference is stationary), Lutkepohl book says: "...in general, a VAR process with cointegrated variables does not admit a pure VAR representation ...
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### expressing a discrete distribution as a mixture of bernoullis

How would one express a discrete distribution as a probabilistic mixture of Bernoulli random variables? An example of a discrete distribution being something like this: $P(X=1)=0.15$, $P(X=2)=0.45$, ...
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### Factor analysis with categorical reponses and missing data

I factor analyzing a measure with 55 categorical items (3 categories each). I am use CFA to test a 7 factor model. I have a very large sample (>10,000), but approximately 20% of the sample is missing ...
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### nonlinear meta-regression

Can someone point me to a basic explanation of theory and methods for fitting nonlinear curves (particularly quadratic functions) to meta-analytic data? I have a set of effect sizes that are clearly ...
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### Do the marginalised posterior and likelihood function converge in the limit of a large number of observations

Short question Do the likelihood function evaluated at the ML estimate and the marginalised posterior converge in the limit of a large number of observations? Long question I expect the two ...
27 views

### Repeated measures ANOVA and uneven number of trials

Suppose I have multiple responses from each subject in three different conditions (A, B, C). If I would decide to run a repeated measures ANOVA, I would first average over the repetitions from each ...
36 views

### What are desirable characteristics of a test statistics?

I've seen definitions of statistics which combine multiple terms in a very specific way. What are advantages of these expression and why not use just any calculation on the data? For example why do ...
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### What are the implications of estimating a covariance matrix from a correlated sample?

Given a sample of $n$ independent observations $x_1,...,x_n$ (where $x_i$ are $p$-dimensional column vectors), the $p \times p$ sample covariance matrix is defined as ...
A random variable $Z$ is the sum of two independent random variables $X$ and $Y$, with known probability densities $f_X$ and $f_Y$, respectively. Now suppose you sample $Z_1=X_1+Y_1$ but you don't ...