The continuous-data tag has no wiki summary.
0
votes
0answers
16 views
Is discretization still the only way to deal with continuous and count variables in data mining association algorithms?
I have recently read a book chapter of data quality in which the author is against turning continuous variables in groups. While I agree with some of his arguments, I was not be able to find a way to ...
0
votes
1answer
32 views
Is this a scale or ordinal variable
I have a questionnaire distributed to the users with the following question from which users can select an answer
Q: What was the project Cost Performance Index
...
0
votes
0answers
15 views
NMDS for biomass
I would like to make a NMDS with biomass of different prey groups in stomach content of fish..
I have already made one where the data matrix consists of 0 and 1, and this one went fine but are not ...
0
votes
1answer
41 views
Statistical test to show association of any kind between two variables
I have two continuous variables which I have data from a physics exspirment.
I want to test for association between the two variables but without assuming a monotonic relationship. I also only have 6 ...
0
votes
0answers
7 views
How to convert contineous variable to descrete in R? [migrated]
I have a variable which encodes group ID:
d <- data.frame(group = c(0,1,0,2,1,3,2,0,1,2), x=c(1.2,2.3,3.2,2.1,1.3,1.5,2.3,0.4,1.3,1.7))
When I try to use it ...
0
votes
0answers
41 views
What is the Net Promoter Score Data Type
As many people know Net Promoter Score is a customer feedback measure calculated from the response to the question: "How likely would you be to recommend [us] to a friend or colleague". The response ...
0
votes
0answers
186 views
How to test correlation between an ordinal and a continuous variable?
Which is the best way to test correlation between what I think it is an ordinal variable (the no of weeks worked out of first 8.. which can take values from 0 to 8) and a continuous variable (the ...
0
votes
0answers
35 views
Non-normal data and non-parametric tests [duplicate]
I have two non-normal variables (one DV, one IV) and a few 7-point Likert scale IVs (normally distributed). The non-normal variables are centrality scores from network analysis - DV is from the ...
1
vote
0answers
91 views
Am I looking at count, ordinal, or continuous data? Using a self-report questionnaire of depression
I am using the PHQ-9, a measure of depression. Here is a link to it:
http://www.waterloowellingtondiabetes.ca/usercontent/documents/PHQ9PatientHealthQuestionnaireforDepression.pdf
I am wondering ...
3
votes
1answer
163 views
1
vote
0answers
45 views
High heteroscedasticity level
My dependent variable - logincome - and one independent variable - age - are continuous. All other explanatory variables are categorical including BA_degree, race, occupation, region, homeownership.
...
2
votes
1answer
109 views
Analogues of sensitivity and specificity for continuous outcomes
How can I calculate the sensitivity and specificity (or analogous measures) of a continuous diagnostic test in predicting a continuous outcome (e.g., blood pressure) without dichotomizing the outcome? ...
1
vote
1answer
579 views
ANOVA or Regression? 1 Continuous factor & 1 Categorical factor with continuous response variables
I have 1 categorical factor (3 treatments) and 1 continuous factor (weight) and then I have 5 continuous response variables.
From what I have read, I should not use a two way ANOVA as one of the ...
2
votes
0answers
46 views
Static Bayesian networks using p-values
In your opinion, what is the best way of handling Bayesian networks using continuous data, in this particular case, p-values?
I have read about several discretization techniques, Gaussian approaches, ...
0
votes
0answers
36 views
How to discretize training and test files to not encounter inconsistency in data?
I have a problem in discretizing my data. My data comprises of two parts: training data and test data. I discretized training data using some parameters of equal-width binning and used the same ...
1
vote
1answer
95 views
Significant regression for the dichotomised predictor variable and not the continuous version of a predictor variable?
I am interested in examining the association between cardiorespiratory fitness and PCA derived dietary pattern scores in 264 adolescents. My cardiorespiratory fitness predictor is vo2max, and my ...
2
votes
1answer
435 views
How to analyse a continuous response having a bimodal distribution?
I am investigating unconscious racial prejudice as a predictor for guilty or not guilty judgements (Using SPSS).
I have a continuous variable for unconscious racial prejudice (higher numbers equal ...
2
votes
0answers
97 views
Inferring transition matrices in continuous time Markov processes
Suppose I have a process X1, for which I do not have a generator matrix, only a transition (probability) matrix P1 for some time interval T, e.g. T=100. Suppose I have another process X2, such that X2 ...
0
votes
0answers
82 views
How to count variables in Cox PH model?
I am doing Cox PHR and I have several categorical, ordinal and continuous variables. Now we did univariate analyses (Log-Rank test) categorizing each continuous variable into 2 categories (based on ...
1
vote
1answer
129 views
Comparing continuous predictors for a dichotomous variable
I have two continuous predictor variables to predict a dichotomous variable. In addition i have constructed two (interaction) models, based on domain knowledge which use both variables to predict the ...
9
votes
2answers
224 views
Computationally efficient estimation of multivariate mode
Short version: What's the most computationally efficient method of estimating the mode of a multidimensional data set, sampled from a continuous distribution?
Long version: I've got a data set that I ...
3
votes
0answers
68 views
Dependent variable maximum value contingent on independent variable
I am trying to create a model for debt collections. In the past I have used logistic regression to predict pay/no-pay. This has worked well but has a few unfortunate consequences. People are more ...
4
votes
2answers
258 views
Probability of two values being equal in a sample drawn from a continuous distribution
I am reading about the Kolmogrov-Smirnov tests from the book Probability and Statistics by DeGroot and Schervish. In the initial few lines on this topic, the authors state the following:-
Suppose ...
0
votes
1answer
200 views
How to perform linear regression with categorical factors? [duplicate]
Possible Duplicate:
How to test the statistical significance for categorical variable in linear regression?
I need to perform a multiple regression analysis. My dependent variable or ...
2
votes
1answer
76 views
Correspondence analysis on a table of means
I have a table of the following kind:
Cat1 cat2 cat3 ...
Var1 6.3 5.3 8.3
Var2 5.2 5.7 6.1
Var3 2.2 3.9 7.6
.
.
.
It is a table of means for ...
1
vote
1answer
135 views
Rare Events Model with a discrete index as the dependent variable?
I'm looking for a rare events model where the dependent variable is a discrete index, which means I cannot use the rare events logit model (Gary King). My dependent variable is an index of integers ...
0
votes
1answer
63 views
machine learning to predict equations / parameters of equations
I'm not sure if machine learning is the best way to do this, but I'm interested in seeing if this problem is feasible. Normally you use machine learning for classification. ie.given the size of a ...
2
votes
3answers
487 views
Binary classification vs. continuous output with neural networks
Wikipedia says in binary classification:
Tests whose results are of continuous values, such as most blood
values, can artificially be made binary by defining a cutoff value,
with test results ...
0
votes
0answers
92 views
Maximum-entropy joint pdf
I have multiple (finitely-many) variables with independent posterior pdfs $f_{x_1}...f_{x_n}$ based on Bayesian updating treating them as independent with independent evidence.
If I subsequently ...
4
votes
3answers
781 views
Clustering a dataset with both discrete and continuous variables
I have a dataset X which has 10 dimensions, 4 of which are discrete values.
In fact, those 4 discrete variables are ordinal, i.e. a higher value implies a higher/better semantic.
2 of these discrete ...
0
votes
1answer
1k views
Predicting with both continuous and categorical features
Some predictive modeling techniques are more designed for handling continuous predictors, while others are better for handling categorical or discrete variables. Of course there exist techniques to ...
4
votes
1answer
348 views
Probability that a quadratic equation with random coefficients has two real solutions?
In the following second order equation $ax^2+2bx+1.5=0$ where $a$ and $b$ are given by random points $(a,b)$ in the $[0,2]\times[0,1]$ rectangle, what is the probability of having two real solutions?
...
1
vote
2answers
2k views
Correlation between dichotomous and continuous variable
I am trying to find the correlation between a dichotomous and a continuous variable.
From my ground work on this I found that I have to use independent t-test and the precondition for it is that the ...
5
votes
1answer
1k views
How to choose between ANOVA and ANCOVA in a designed experiment?
I am conducting an experiment which has the following:
DV: Slice consumption (continuous or could be categorical)
IV: Healthy message, unhealthy message, no message (control) (3 groups in which ...
3
votes
2answers
558 views
Comparing odds ratios of continuous and discrete variables
I need to compare the ability of two methods to predict an event with a binary response. Each method produces a score, where the higher score indicates 1 and a lower score indicates 0. I am looking to ...
5
votes
1answer
209 views
Incremental training of Neural Networks
Is it valid to train a neural network over and over again with new arriving data (including pruning after each new training)?
I plan to collect data for a period of time, train/cv/test the networ, ...
1
vote
1answer
488 views
Interaction terms interpretation
How do you interpret an odds ratio of an interaction between two continuous variables $x_1, x_2$? Would you fix $x_2$ and let $x_1 = x$ and $x_1 = x+1$?
1
vote
0answers
196 views
Using controls as basis for quantile/tertile categorization
I have a number of continuous but really skewed variables in the statistical analyses I am currently performing. Even though I am strongly in favour of keeping them just as they are and relaxing ...
0
votes
1answer
189 views
Bayesian updating of continuous variables given mutual information
I have very little stats training, so this may be a very obvious and boring question, in which case I apologise.
Given two real-valued continuous random variables A and B, and given prior probability ...
0
votes
1answer
631 views
How to visualize an interaction effect from a regression?
I have a regression with a harmonic effect of day of the year, which interacts with other variables. I am not sure how to interpret the coefficients. My model is:
...
0
votes
1answer
193 views
Discretize frequency of words that follow zipfian distribution
How could I discretize the frequency of words found in a corpus that follow a zipfian distribution? Are there standard methods? It should create bins of exponential-increasing size.
My goal is to ...
2
votes
0answers
45 views
Calculating probability of discovery
I have a planner that can evaluate N arbitrary states, and calculate their fitness. The domains it evaluates have no explicit "end state", so it has an infinite horizon.
What are good methods for ...
2
votes
1answer
304 views
Do the properties of Pearson's chi-squared test for independence hold true for continuous PDFs?
In probabilist statistics, the properties of a discrete Pearson's chi-squared test hold that:
\begin{aligned}
\chi^2 = \sum_{i=1}^{r} \sum_{j=1}^{c} {(O_{i,j} - E_{i,j})^2 \over E_{i,j}}
...
6
votes
2answers
212 views
Best practices when treating range data as continuous
I am looking at whether abundance is related to size. Size is (of course) continuous, however, abundance is recorded on a scale such that
...
1
vote
1answer
152 views
Continuous-states hidden Markov chain
How to deal with HMC that has continuous states?
Any papers, links, materials that explain the solution?
1
vote
2answers
347 views
Can I use log-likelihood distance on data of only continuous variables?
I have to run a SPSS two-step cluster analysis. All my 4 variables are continuous scalar standardized parameters (with normal distribution). The dataset includes 10,000 cases.
SPSS suggest to use ...
1
vote
1answer
222 views
NAs in summary of linear model generated from significant genes for continuous response variable identified using SAM
I have a gene expression data-set with log2-transformed expression values (no NAs) for 495 genes for 59 samples for which values of a continuous response variable (r) are also known (no NAs). I want ...
2
votes
0answers
64 views
Density related to sparseness measure
Are there any multi-variate continuous distributions whose probability distribution functions give high values for sparse vectors and low values for dense vectors, i. e. indicating the sparseness of ...
1
vote
1answer
277 views
Why are most standard goodness of fit tests based only on continuous distributions?
I tried to search info regarding this fact but I don't really understand why most of the standard goodness of fit tests (e.g. Kolmogorov-Smirnov, Anderson-Darling, a part of the Chi-square test, ...
1
vote
1answer
791 views
Can random effects apply only to categorical variables?
This questions might sound stupid, but... is it correct that random effects could apply only to categorical variables (like individual id, population id, ...), e.g. say $x_i$ is categorical variable:
...
