Categorical data can take on a "limited" (usually fixed) number of possible values. Not to be confused with `factor-analysis`.
0
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0answers
10 views
Reduce Sample Size (Categorise??) [duplicate]
I have been looking for an answer to my question but havn't been able to find any literature documentation or help in regards. I have a large dataset which I need to further analyse. Because of this I ...
0
votes
3answers
33 views
Clustering mixed variables in SAS
I have following variables in my dataset:
Working hours (numerical:ordinal)
Effectiveness (categorical:ordinal ; 4 values-> (poor,average,good,best))
Satisfaction (categorical:ordinal ; 4 values-> ...
1
vote
2answers
60 views
Dummy variables in multiple regression, why use an intercept?
When performing a multiple regression with dummy variables, is it really necessary to include an intercept term in the design matrix?
By dummy variables, I mean indicator variables; a one in the ...
1
vote
0answers
20 views
MR with dummy variables
I need to calculate MR but my data consists of many dummy variables. I had a question in my survey that asked for the budget/month. But instead of giving the option to fill in a value, I offered ...
1
vote
1answer
30 views
Categorical value “stuck” during sampling of my model
I'm having some troubles with the implementation in pyMC of my probabilistic model.
Note: you can skip directly to the code section, if you're not interested on the use of the model.
The model ...
3
votes
1answer
99 views
Dummy coding for contrasts: 0,1 vs. 1,-1
I'm seeking your help in understanding the difference between two different contrasts for dichotomous variables.
On this page:
http://www.psychstat.missouristate.edu/multibook/mlt08.htm
under ...
0
votes
0answers
42 views
ARIMA forecasting with external regressors
I am trying to build ARMAX models using auto.arima. I have a time series to forecast (weekly and monthly seasonality, I've put the ts() frequency=7), another two time series as external regressors, ...
2
votes
1answer
113 views
+100
Select best set of binary variables for clustering known sample labels
I have a set of samples, for which I know the "true groups". For this samples I have about 200 binary variables, I would like to know a method to select the subset of variables, that gives me a ...
3
votes
0answers
52 views
Variable selection / Dataset reduction for large datasets (in R)
I'm working on a behavoural scorecard modelling exercise, and many of the decisions taken to date have been based on the experience of a consulting credit analyst (whose experience software-wise is ...
1
vote
1answer
39 views
ARIMA and external regressors in SAS and R
So I remember reading somewhere that when we have external regressors, auto.arima cannot make correct predictions for the order of difference for either ...
0
votes
1answer
46 views
Conditional expected value from a regression model using ordinary least squares
I have a query regarding part (a) of the following question. I cannot figure out how to calculate the conditional expected value of collections for the month of Easter. Is it not possible to calculate ...
2
votes
0answers
38 views
Dummy variables for time series
I'm a new user on R. I'm stuck on my times series research currently with the some questions. Not sure anyone can help me.
Dummy variable.
I wanted to add more than 1 dummy variable in the model. ...
0
votes
0answers
25 views
Plot normal probability for effect estimates in factorial design in R
I have 2 level Design (DOE) with 4 factors (A,B,C,D). I've already calculated the estimates for each main effect and all the interaction effects.
How can I construct the normal probability plot to ...
1
vote
0answers
10 views
Dummy variable as side constraint in DEA
What do you think these dummy variables do to the resulting weight values in a BCC/VRS data envelopment analysis? It appears the 1 and -1 relations drive the program to make the weights for the ...
0
votes
0answers
42 views
Distance Metrics For Binary Vectors
I have vectors of same length consisting of 1 and 0. I am trying to find out how similar they are. So far I am using hamming distance that I calculate sum of one vector then sum of second vector and ...
0
votes
0answers
23 views
Setting indicator variables to equal 1 or 0 [migrated]
I have to set HIGPA to equal 1 if the gpa is greater than 3, and if it is less, then HIGPA must equal 0. I am using R.
gpa is already a variable in the data. HIGPA is not.
So far I have made HIGPA a ...
0
votes
1answer
41 views
Is it required for panel data to use dummy variables?
I am doing a research considering seven countries and I have panel data. My question is: do I need to include dummy variables every time I use panel data in regression, or is enough to do it as a ...
1
vote
0answers
19 views
Reference Group for dummy coding [migrated]
Is there any way to explicitly specify which group to take as reference group for dummy coding when modeling with lm function in R using categorical variables??
1
vote
1answer
41 views
Dealing with Dates of Birth in Predictor
I have a predictor variable of type factor which contains the date of birth.
From your experience (when dealing with logistic regression), what is the best way of treating date of birth (or similar ...
0
votes
1answer
25 views
Need help selecting test for nominal IV with categorical DP
I am going to attempt to give you as much background as possible.
My independent variable is nominal and describes the number of days after which an insect was exposed to new conditions (0,1,3,5,7).
...
0
votes
1answer
22 views
How do I derive slope and intercept for each group in regression model with a categorical and 2 continuous predictor variables?
$IQ = b_0 + b_1Group + b_2Age + b_3Income + b4\times Group\times Age$
Group is dummy coded ($0,1$)
I assume that the interaction of Group x Age tests the group difference in the slope of the IQ vs. ...
0
votes
1answer
55 views
What method can be used to test if three or more categorical sample data sets are from the same distribution?
I have three data sets like this:
data1: {A, A, B, C, D, ..}
data2: {A, B, B, C, E, ...}
data3: {A, C, D, D, E, ...}
How do I test if these three data sets are from the same distribution?
1
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0answers
22 views
Including seasonal dummies in regression
I've downloaded some data. Problem is some of them have been seasonally adjusted while the rest have not. I could not find data that have all been seasonally adjusted.
Wonder if I run a regression ...
2
votes
1answer
43 views
What factor (trials or blocks) to use in a repeated measures ANOVA
I am conducting a psycholinguistic experiment. Each trial consists of the subject responding to a word by pressing a button.The design of my experiment is as follows:
5 blocks of a 100 trials each ...
0
votes
0answers
32 views
Simplfying summary statistic output stratified by a categorical variable in R [migrated]
Program being used
I am using the statistical program R to analyze some data and have what is likely a fairly simple question.
Background to the problem
I have a variable full of numeric values ...
0
votes
2answers
187 views
Best method to analyse survey results with multiple choice of answers
I have designed a survey with multiple choice answers. Each question contains same set of answers
Strongly agree
Agree
Disagree
Strongly disagree
Don't know
There are 25 questions and ...
0
votes
0answers
17 views
Prepare data for generalized linear regression [migrated]
I want to perform glm for the dataset Titanic in R. I did the following steps to prepare the data and run glm
...
0
votes
0answers
37 views
Multiple Regression questions (restricted regression, dummy variables)
Q1.
Model 1: $Y=X_1\beta_1+\varepsilon$
Model 2: $Y=X_1\beta_1+X_2\beta_2+\varepsilon$
(a) Suppose that Model 1 is true. If we estimates OLS estimator $b_1$ for $\beta_1$ in Model 2, what will ...
0
votes
1answer
33 views
spss: working with two binary/dummy variables
Am trying to set a few binary/dummy variables against each other, i.e. propensity_to_dance and gender.
I assume that it' ok to ...
1
vote
1answer
53 views
How to analyze ordinal repeated measures data
I have data from an ordinal scale, with the score ranging from 1-4. Each subject has 9 assessments on this scale (study is a 9-way crossover design), and there are no missing data. What is the ...
1
vote
0answers
15 views
Log-linear analysis vs Breslow-day test
I would like to test independence of several categorical variables for a few datasets. I believe Breslow-day is possible for some of the analyses I want to do, and log-linear may be possible for all, ...
1
vote
1answer
29 views
Distance measure for multi-categorical responses
I have a data set of categorical data where each question can have more than one answer. This is a toy example:
question one: what did you eat today?
...
0
votes
0answers
22 views
Preparation of categorical data for hierarchical clustering
I would like to use R to perform a hierarchical clustering of data that looks like this:
L1 L2 L3
F1 p pr r
F2 p NA r
which is supposed to ...
1
vote
1answer
51 views
How to eliminate high multicollinearity with a continuous moderating variable, and a categorical independent variable
I am looking at whether Corporate Venture Capital-backed firms (1) perform better than Independent Venture capital - backed firms(0) in their POST-IPO performance. My assumption is that this ...
0
votes
1answer
52 views
When is it valid to include interaction terms in a regression model? [duplicate]
I am using logistic regression to analyze some categorical data (binary response variable and categorical -- mostly binary -- predictor variables). For my model, I have something like ...
3
votes
1answer
163 views
Interpreting interaction terms in logit regression with categorical variables
I have data from a survey experiment in which respondents were randomly assigned to one of four groups:
...
0
votes
1answer
73 views
Regression using dummy variables
I am working on a credit scoring modelling project and we decided to use dummy variables for regression. The way we create dummy variables are:
For each predicting numeric variable,
We create by ...
1
vote
1answer
34 views
Categorical or continuous variable?
Suppose that in a linear regression, some of the continuous variables (such as number of pills taken each day) have small discrete values. For e.g. the number of pills taken each day can take values ...
1
vote
2answers
45 views
Attempting to investigate a relationship between one variable and another that has three possible values
I'm looking to investigate the relationship between a series of variables on a recurring basis.
One variable will always be the dependent variable, and will take three possible values: ...
1
vote
1answer
41 views
Testing equality of proportions
I am comparing three proportions for age categories for categorical variables that have also categories.
I used Chi-square test but I found that SPSS gave me a note which is for example:
a. 2 cells ...
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 ...
3
votes
1answer
50 views
Fisher's exact test, contingency tables
Are there any other methods for an $m\times n$ contingency table with $m$ or $n$ greater than 2 for use with small samples ($np<5$) other than Fisher's exact test?
3
votes
2answers
142 views
Getting rid of a huge categorical factor in multiple regression
I have a large regression problem with a lot of cases, but relatively few independent variables. One of them is a categorical factor with thousands of levels. Robust regression runs forever. In some ...
1
vote
1answer
47 views
Dummycoding based on clustering from OM distances
I'm using TraMineR to determine a certain clustering based on Optimal Matching distances:
...
1
vote
0answers
84 views
Help analyzing repeated measures categorical data
This is my first post. I have the following data set-up: I asked 331 subjects about whether or not they would take a drug to enhance the following four domains/abilities: Cognition, Mood, Sex, and ...
0
votes
0answers
49 views
Variables selection (continuous and classification): how to do in R?
My dataset have both classification (categorical) and continuous variables, ~ 300 variables in all. I'm looking for a way to reduce my attributes to be less than 300 and put them in the decision tree ...
0
votes
0answers
71 views
Analysis to use with categorical response and categorical predictor variables
I have data from a randomized survey experiment in which each respondent was assigned to one of 4 groups, one of which can be considered a "control" or "no treatment" group. The key question asked in ...
4
votes
1answer
84 views
Dealing with 'Don't Know' answers for a categorical outcome variable
I have a survey data with categorical outcome variable (yes, no, don't know) which reflects the acceptance of some situation by respondents. My concern is how to deal with Don't know answers, I really ...
0
votes
0answers
23 views
weighted regression with dummy variables [duplicate]
I am looking for some references on weighted regression when we have only dummy variables for predictors. I would appreciate it. Thanks.
2
votes
2answers
118 views
How to visualize counts of different categories
Suppose we have $10$ boxes and we are interested in measuring the number of apples, oranges and pears in each. What is a good way to visualize how the boxes relate to each other in terms of the ...
