Latent variables refer to variables that cannot be directly observed. These variable are defined in terms of observable variables.

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1answer
35 views

When a CFA model has a “covariance matrix was not positive definite” problem, is it due to the dataset or the model?

I am testing several CFA measurement models with Lavaan in R. The questionnaire that I am investigating has been shown to be composed of 1-factor, 3-factor, and 4-factor. In the dataset, I found ...
-1
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0answers
11 views

How do i perform taxometric analysis [closed]

i want to perform taxometric analysis?i have source R taxometric but i have problem about how to input data and do the command analysis
3
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1answer
115 views

Combining several variables into one outcome score: How is it done in the machine learning community?

I have got 8 cognitive (continuous) behaviour variables and would like to combine them into a composite score. I would then like to find the best predictors of this outcome (from about 50 predictors). ...
1
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1answer
38 views

Easy and common way to separate latent classes from Likert-scale survey?

Let say, there are two 5-points Likert-scale questions "How do you like a flavor?" applied for two product samples. That is, each respondent tries two samples and evaluate them on Likert scale. ...
0
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0answers
11 views

JAGS: multivariate normal with both, unobservable and observable variables? [migrated]

I have a "simple" problem with JAGS that drives me crazy. In essence, consider the following example that works: ...
0
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1answer
39 views

Mean field variational inference

In Chris Bishop PRML book p.465 equation 10.6, the derivation doesn't explain why exactly the term $\int q_j ln(q_j) dz_j $ was generated, is not that term supposed to be multiplied by constant, did ...
0
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0answers
12 views

How do you correctly scale a formative latent variables in a structural equation model?

How does one scale a formative latent variable? I know that one option is to multiply one indicator by 1. What I do not understand is that if depending on which indicator is multiplied the direction ...
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0answers
27 views

Comparing a model with a latent variable to one without

I would like to test whether my 3 dependent variables all load onto an underlying latent variable or if a latent variable is not necessary to explain the relationship between the IVs and the DVs. In ...
1
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0answers
23 views

Explain: Latent Variable (e.g for Latent Dirichlet Allocation)

I am trying to understand the Latent Dirichlet Allocation but therefore I need the basic understanding about what exactly a latent variable is in that sense. I know that the basic idea of a latent ...
0
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0answers
20 views

Sparse PLS: algorithm for variable selection and model fitting

In the spls package in R (based on the manuscript by Chun and KeleĊŸ [1]), there is a separate specification for the variable selection and fitting in the main function, ...
0
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0answers
18 views

Latent growth model with differing outcome measures across time points

I'm hoping to fit a latent growth model in a situation where the availability of outcome measures changes across time points. Specifically, looking at antisocial behaviour in developing youth where ...
0
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0answers
12 views

Should the rivals models include the same number of observed variables?

The question is about comparing models that include different number of observed variables. For example consider I have an 80-items questionnaire and I want to do confirmatory factor analysis (CFA) in ...
5
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3answers
154 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 ...
1
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1answer
23 views

Confusing definition of Potts model

I came across some Markov random field models and noticed something that didn't make sense to me. One of these models for a set of latent variables $\{z_{i}\}$ is the following: $$p(z) = ...
0
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0answers
28 views

Ways to express the relationship between a latent variable and observables

How do I express concisely the idea that the values of a number of observables is determined stochastically by the value of a latent variable? Can I say: The value of the latent variable is ...
0
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0answers
27 views

Conceptual links and differences between generalized and latent models

Please bear with me, as I'm trying to better understand these aspects. My understanding is that (finite) mixture models (MM) are characterized by a presence of a number of sub-populations in a ...
1
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0answers
32 views

Mixture distribution fitting for latent variable analysis

Are there any analytic approaches to using mixture distribution fitting for latent variable analysis? I'm specifically interested in existing approaches to determining whether mixture components ...
2
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1answer
58 views

What is the role/purpose of hidden variables in graphical models?

Is there a formal treatment of the role/power of latent/hidden variables in graphical models and other machine learning models (e.g., structural equation models)? For example, the Restricted Boltzman ...
0
votes
1answer
44 views

identifying latent variables in this model

I have been trying to understand EM and I am having a hard time understanding what a latent variable is. In particular, I am having issues in identifying whether in a particular model that I am using, ...
4
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2answers
179 views

How to choose an optimal number of latent factors in non-negative matrix factorization?

Given a matrix $\mathbf V^{m \times n}$, Non-negative Matrix Factorization (NMF) finds two non-negative matrices $\mathbf W^{m \times k}$ and $\mathbf H^{k \times n}$ (i.e. with all elements $\ge 0$) ...
0
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0answers
19 views

How to model occurrence counts in groups with latent membership?

I have a dataset that describes the daily history of occurrences of a certain phenomenon P among a certain population. (These are subdivided into certain classes or forms that the phenomenon can take: ...
2
votes
1answer
84 views

How to use factors (from CFA) as independent variable in Regression Analysis

I calculated 4 factors as latent constructs in a Confirmatory Factor Analysis (I use AMOS). Now I am wondering if it is possible to extract some kind of a factor score like I know it from Exploratory ...
1
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2answers
124 views

Binary version of Probabilistic Matrix Factorization in pymc?

I'm a newby in statistics, this is my first post, sorry for any possible mistake. There is a good Bayesian Probabilistic Matrix Factorization model introduced in: Bayesian Probabilistic Matrix ...
0
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0answers
17 views

Mixture model for dependent observations with additive group-level confounders

I'm looking for a special type of mixture model (described below) and I'm hoping to get some hints with regards to relevant literature to look at or names to be searching for. On the general level, ...
0
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0answers
60 views

Estimation parameters for latent (unobserved) variable

Here is my problem: I have 3 variables $X,Y,Z$ : $X$ is the number of clicks we observed on an web advertisement; $Y$ is the number of time a customer do a sign-up on the website after clicking ...
0
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2answers
93 views

Partial Least Squares structural equation modeling

Im calculating a Structural Equation model with Partial Least Squares (with R). Lets say a simple example: two Response values (R1, R2) are combined to a latent variable RespLV = weight1*R1 + ...
0
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0answers
24 views

How to compute a latent variable (as a composite index)

Can I calculate a latent variable (construct) after the formula: Sum of (summated scale for factor i * variance explained by factor i), i taking values from 1 to n (n being the number of factors)? Or ...
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0answers
33 views

Summated scales for factors (latent variables)

For summated scales: can I use all the variables that load on a factor or is it necessary to use only the variables with high loading (over 0.70, for example)?
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0answers
14 views

Summated scales (after factor analysis)

Is it okay to calculate summated scales if I am undertaking an exploratory study and some of the factors that result are somewhat different from what I have found in the literature? (I have read that ...
2
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0answers
47 views

latent variables versus model parameters

I am quite confused with the distinction between a latent variable and model parameters. So say I have two observed variables $x$ and $y$ and they have some unknown relationship between them i.e. $y ...
0
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0answers
22 views

Splines, latent variables and model identification

For $J$ units of observations my basic model contains latent variables $\theta_j, j = 1, ..., J$ identified by the marginal assumption $\theta \sim N(0,1)$. The latent variables are connected to a ...
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0answers
14 views

Is there an extension of multinomial process models that can model several dependent variables?

In the setting of psychological experiments, where a categorical response has to be given, the same response can, in theory, be generated by different latent processes. For example, in an experiment ...
0
votes
1answer
88 views

Bayes' theorem in 1-d EM algorithm

I'm watching a video on the EM algorithm, When we use Bayes' Theorem to calculate $b_i$, how do I find $P(b)$ and $P(a)$ initially? It says we can estimate the priors $P(b)$ and $P(a)$ but that's ...
4
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2answers
145 views

EM algorithm Practice Problem

This is a practice problem for a midterm exam. The problem is an EM algorithm example. I am having trouble with part (f). I list parts (a)-(e) for completion and in case I made a mistake earlier. Let ...
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2answers
96 views

Can I test hypothesis based on estimated parameters?

I estimated the mean and variance of two latent variables through two groups of data. I can't use the data to do hypothesis testing, because I am interested in the latent variable. Is there a way to ...
0
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0answers
156 views

The difference between SVD and SVD++

What if any is the connection between SVD (the one you learn about in your linear algebra course) and SVD++ (the one from the Netflix prize)? I know they both want to find latent factor spaces. But ...
0
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2answers
141 views

Compute the user and item features in SVD++

I have a sparse matrix. There is lots of missing data. Hence, I can't use SVD naively. I read Koren's SVD++ paper. I'm confused as to how the $q_i$ and $p_u$ vectors are determined. $q_i^Tp_u$ is ...
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0answers
47 views

Use of latent semantic analysis in topic modeling

I am learning Latent Semantic Analysis. After we have the SVD decomposition of term-document matrix, how to infer topics from that? For example, how to get the following result: Topic 1: apple, ...
0
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0answers
57 views

How to make the most of a Gaussian mixture assumption in a model?

I have a dataset with 100 columns and approximately 100000 lines. I have a variable to predict that is Y (0,1 so it's a classification problem). I have an other categorical variable with two values ...
1
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0answers
75 views

Log Transformation in Growth Mixture Model (Mplus user)

I am using parallel process growth mixture modeling to estimate bidirectional longitudinal dynamics between pain (0-100 theoretical range of values) and sleep measures (0-20 theoretical range of ...
4
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2answers
120 views

Are there any good papers comparing different philosophical views of cluster analysis?

Lots of people use cluster analysis. I've heard very few explicitly say why. I imagine this is because within a given field, most researchers seem to understand why clustering is used for the problems ...
3
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1answer
106 views

Variational Posterior Dirichlets in LDA

I am running the c code for LDA provided on David Blei's website. The code outputs several files. The output file final.gamma is supposed to include the "Variational Posterior Dirichlets". If I ...
0
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0answers
30 views

Convert latent proabilities to categorical realizations

Assume that each person can only have one of three eye colors: blue, brown or green. Furthermore assume that I have two vectors that describe for N individuals the (simulated) probability that the ...
0
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2answers
64 views

Can I turn a latent variable be treated as an observed variable?

I am a doctoral candidate and for my dissertation research I am using two standardized scales as independent variables. Because these have not been used with my particular population, I needed to do ...
0
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0answers
24 views

Categorical observed, Binomial latent

This might be a trivial problem but wondering if there's a known model formulation for this problem: Ordered Categorical observed variable with k levels Trying to estimate the parameter (theta) of a ...
2
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2answers
83 views

What happens when you initialize EM with a consistent estimate?

I have a certain family of models with latent random variables (not observed in the data), which I have a consistent estimator for. I now run EM on top of it, meaning, I get the consistent ...
3
votes
1answer
158 views

What are the main differences between classical and Gibbs sampling Latent Dirichlet Allocations?

In these weeks I have been studying the classical Latent Dirichlet Allocation (LDA) algorithm by David Blei and colleagues (2003), and the LDA variant based on Gibbs sampling introduced by Tom ...
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0answers
43 views

Map a normal distribution N(x,s) to an ordinal response variable

I am working on a simulation. I am going to extract a series of normally distributed values from a distribution $N(x,s)$ whose mean $x$ and variance $s$ is known. I want to pretend that such ...
2
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1answer
85 views

Latent Dirichlet Allocation - understanding the posterior

I have a problem understanding the posterior for computing LDA, stated in page 7 of Blei (2007). From my point of view, it's not exactly consistent with Bayes' theorem, as described here. Could anyone ...