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Topic: Categorical variable

	What is the difference between categorical, ordinal and interval variables?
		An ordinal variable is similar to a categorical variable.
		An interval variable is similar to an ordinal variable, except that the intervals between the values of the interval variable are equally spaced.
		Sometimes you have variables that are "in between" ordinal and interval, for example, a five-point likert scale with values "strongly agree", "agree", "neutral", "disagree" and "strongly disagree".
	www.ats.ucla.edu /stat/mult_pkg/whatstat/nominal_ordinal_interval.htm (940 words)

	COMPLEX (FACTORIAL) DESIGNS: A CONCEPTUAL OVERVIEW
		The categorical variables can be independent variables (i.e., manipulated by the investigator) or subject/correlational variables (i.e., non-manipulated variables measured by the investigator).
		A MAIN EFFECT is the unique effect that 1 categorical variable had on the dependent variable, regardless of the level of the other categorical variable(s).
		A main effect is calculated by averaging the score on the dependent variable at each level of one categorical variable.
	otel.uis.edu /yoder/fact_conc.htm (548 words)

	SPLUS/R Library: Coding systems for categorical variables
		Categorical variables require special attention in regression analysis because, unlike dichotomous or continuous variables, they cannot by entered into the regression equation just as they are.
		The second comparison compares the mean of the dependent variable level 3 of race with both levels 1 and 2 of race, and the third comparison compares the mean of the dependent variable for level 4 of race with levels 1, 2 and 3.
		Which level of the categorical variable is assigned a positive or negative value is not terribly important: 1 0 -1 0 is the same as -1 0 1 0 in that both of these codings compare the first and the third levels of the variable.
	www.ats.ucla.edu /stat/r/library/contrast_coding.htm (3946 words)

	Variable Types
		Categorical variables take a value that is one of several possible categories.
		I'd classify this variable as categorical; it would not be entirely incorrect to classify it as quantitative.
		The response variable is quantitative, the explanatory variable is categorical.
	www.oswego.edu /~srp/stats/variable_types.htm (815 words)

	Categorical Variables (Site not responding. Last check: 2007-10-08)
		In the Variables box of the Analysis Page, the categorical variables are identified by [C] at the end of the label.
		The Common Category Variables (always shown on top in the Variables box of the Analysis Page), such as size, exporter or ownership, are the typical examples of categorical variables.
		In statistical procedures, such as Means, categorical variables are treated as if each category had a numeric value assigned to it.
	iresearch.worldbank.org /ics/Help/categorical.htm (198 words)

	[No title] (Site not responding. Last check: 2007-10-08)
		A categorical predictor variable is a variable, measured on a nominal scale, whose categories identify class or group membership, which is used to predict responses on one or more dependent variables.
		This categorized plot is constructed in the same way as the standard normal probability plot for the categorized values, except that before the plot is generated, the linear trend is removed.
		The categorized half-normal probability plot is constructed in the same manner as the standard normal probability plot, except that only the positive half of the normal curve is considered.
	www.statsoft.com.cob-web.org:8888 /textbook/glosc.html (7574 words)

	Kipling - Categorical Variable Example (Site not responding. Last check: 2007-10-08)
		The prediction of a categorical variable will be illustrated using logs from the Lower Cretaceous in the Jones #1 well in north central Kansas.
		Kipling requires that categorical values be specified as integers ranging from 1 to the number of categories.
		We now need to specify the discretization of the predictor variable space, as described in the theoretical background section and in the continuous variable prediction example.
	www.kgs.ku.edu /software/Kipling/CategoricalExample.html (428 words)

	PA 765: Multiple Regression
		In this case the F-test of the significance of the interaction of the two variables is the significance of the change of R-square of the equation with the interaction terms and the equation without the set of terms associated with the ordinal variable.
		Thus for the set of dummy variables for "Region," assuming "North" is the reference category and education level is the dependent, a b of -1.5 for the dummy "South" means that the expected education level for the South is 1.5 years less than the average of "North" respondents.
		The variance of the residuals is the estimate of error variance, assuming all relevant variables are in the equation and all irrelevant variables are omitted.
	www2.chass.ncsu.edu /garson/pa765/regress.htm (19068 words)

	Decisions at Hand
		The purpose of this transformation is categorization of a numerical variable to a new, derived, categorical variable.
		Variable age is categorical, but here indices are used instead (two categories, one with index 0 and the other with 1, by default).
		Notice that there should be a variable heat that should be defined and instantiated such that its values should be anything from 0.0 to 1.0 (golf_heat.xml is an example where such a model and associated transformation is used).
	www.ailab.si /app/palm/xml-description.htm (3866 words)

	spss guide (Site not responding. Last check: 2007-10-08)
		For categorical and ordinal data the Mode (though a crude measure) is an appropriate measure of central tendency and the range is an appropriate measure of variability.
		One of the acceptable patterns is for all the populations variances to be identical and for all bivariate correlations to be identical.
		To examine whether or not there is a statistically significant difference in means on some dependent variable (continuous) due to the influence of two independent variables (categorical) you can use the two way analysis of variance procedure when you have two or more levels (unrelated) of each independent variable.
	www.geolog.com /gmsmnt/gmspss.htm (7967 words)

	Categorical Dependent Variable Models Using SAS, STATA, LIMDEP, and SPSS
		The categorical variable here refers to a variable that is binary, ordinal, or nominal.
		When the dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient.
		The QLIM (Qualitative and LImited dependent variable Model) procedure analyzes various categorical and limited dependent variable regression models such as censored, truncated, and sample-selection models.
	www.indiana.edu /~statmath/stat/all/cdvm/cdvm1.html (838 words)

	FAQ: Tests comparing levels of a categorical variable after anova or regress
		There are several variations of the syntax for test depending on if you wish to test coefficients, expressions, terms (after anova), or to test several coefficients at the same time.
		When there are two (or more) categorical factors in our model, we again may want to test various single degree-of-freedom hypotheses that compare various levels of the two (or more) factors in the model.
		In the cell means ANOVA model, we first create one categorical variable that corresponds to the cells in the two-way table (or higher-order table if more than two categorical variables are involved).
	www.stata.com /support/faqs/stat/test1.html (4330 words)

	Disaggregating Data
		The achievement gap is an excellent example of disaggregated data, as it shows how differently students perform on standardized tests (the dependent variable) according to which ethnic group they belong (the categorical variable).
		This variable can be a numeric variable or a string variable (glossary).
		Some examples of common categorical variables in schools are ethnicity, gender, grade level, ELL status, socioeconomic status, and learning disability status.
	www.ezanalyze.com /help/disaggregate.htm (456 words)

	Term: Categorical Variable (Site not responding. Last check: 2007-10-08)
		A Categorical variable is a variable whose outcomes are members of a category.
		If a variable's outcomes are non-numerical then the variable is categorical.
		If a variable's outcomes are numerical then it is categorical if it has no associated unit of measurement.
	www.public.coe.edu /~gcross/toolkit/glossary/glsry-18.html (42 words)

	EXCEL: Regression with Categorical Dependent Variable (Site not responding. Last check: 2007-10-08)
		Then the dependent variable Y is a categorical variable that takes value 1 if employed and 0 if not employed.
		The regressors X are determinants such as age and years of schooling.
		These data are categorical and might be coded 0, 1 and 2.
	cameron.econ.ucdavis.edu /excel/exlpm.html (333 words)

	Regression of Categorical Variable
		Posted on: Monday, 26th April 2004, 1:25 PM For a questionnaire data where the dependent variable is also categorical as well as independent variables are categorical, how to carry out regression.
		The number of variables will be taken care of with a suitable data-reduction technique, so we need not worry on how many independent variables...
		Re: Regression of Categorical Variable by SSS Trainer on Thursday, 3rd June 2004
	www.isixsigma.com /forum/showmessage.asp?messageID=44796 (311 words)

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