
	Where results make sense

Topic: Ordinal variable

Related Topics

Ordinal measurement

	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)

	New View of Statistics: Ordinal Dependent Variables
		Variables like this are called ordinal, because they indicate an ordering of responses.
		But if we try to treat it as a numeric variable, we might violate one or more of the assumptions we make when we calculate confidence limits or p values.
		As I pointed out earlier, the rare situations occur when the responses of a Likert-type variable are almost all stacked up on the top or bottom level of the scale.
	www.sportsci.org /resource/stats/ordinal.html (374 words)

	Social Studies 201 (Site not responding. Last check: 2007-09-21)
		The reason the type of measurement, or scale, differs for different variables is related to the nature of the phenomenon being investigated and to the manner in which the concept being measured is defined (theoretical and operational issues).
		Associated with an ordinal scale are the words “more than,” “greater than,” “less than,” and “equal to.” That is, for a characteristic that is measured on an ordinal scale, any member of a population has more than, less than, or equal amounts of this characteristic, as any other member of the population.
		Variables with an interval scale of measurement have a well-defined unit of measure, so that distances between values of a variable can be meaningfully measured.
	uregina.ca /~gingrich/s1703.htm (5731 words)

	PA 765: Correlation
		Also, there is partial correlation, which is the correlation of one variable with another, controlling both the given variable and the dependent for a third or additional variables.
		Eta, the coefficient of nonlinear correlation, known as the correlation ratio, is discussed in the section on analysis of variance.
		The significance level of a correlation coefficient for the correlation of an interval variable with a dichotomy will be the same as for an ANOVA on the interval variable using the dichotomy as the only factor.
	www2.chass.ncsu.edu /garson/pa765/correl.htm (3727 words)

	Delphi 5 Object Pascal Language Guide: Data types, variables, and constants (Site not responding. Last check: 2007-09-21)
		Whenever a long-string variable is destroyed or assigned a new value, the reference count of the old string (the variable's previous value) is decremented and the reference count of the new value (if there is one) is incremented; if the reference count of a string reaches zero, its memory is deallocated.
		A variant occupies 16 bytes of memory and consists of a type code and a value, or pointer to a value, of the type specified by the code.
		When a variant containing a variant array is assigned to another variant or passed as a value parameter, the entire array is copied.
	info.borland.com /techpubs/delphi/delphi5/oplg/datatype.html (11090 words)

	Wine HQ
		Variable ordinals Syntax: ordinal variable [flags] exportname ([data...
		Extern ordinals Syntax: ordinal extern [flags] exportname [symbolname] This declaration defines an entry that simply maps to a C symbol (variable or function).
		It makes the name and ordinal available for dynamic linking, but will terminate execution with an error message if the function is ever called.
	www.winehq.org /site/docs/winebuild (1739 words)

	SDA DATA TYPES
		On the contrary, every ordinal variable can be regarded as merely a special type of nominal variable (satisfying the condition of having an order), and every interval variable can be regarded as merely a special type of ordinal variable (satisfying the additional criterion of having a fixed distance between successive categories).
		Because every interval variable is also an ordinal variable, a statistical test for ordinal variables can also be applied to interval variables, and because every ordinal variable is also a nominal variable, a statistical test for nominal variables can also be applied to both ordinal and interval variables.
		For any ordinal variable, it is meaningful to consider high and low values, so it is meaningful to talk about positive or negative relationships with other variables which are of ordinal or interval type.
	demography.anu.edu.au /Publications/SDA-course-notes/sec02.htm (3680 words)

	CHAID
		The predictor variable used to form a partition is chosen to be the variable that is most significantly associated with the dependent variable according to a chi-squared test of independence in a contingency table (a cross-tabulation of the predictor and dependent variable).
		Ordinal predictors are allowed to be continuous, rather than categorical, but the amount of computer time and memory increases with the number of different values.
		There must be enough memory to store contingency tables relating the dependent variable to each predictor; the minimum number of bytes required is thus eight times the number of categories for the dependent variable times the sum of the number of categories of all the predictors.
	www.stat.lsu.edu /faculty/moser/exst7037/treedisc.html (3540 words)

	Ordinal Distance Tutorial (Site not responding. Last check: 2007-09-21)
		Ordinal scale play very important role in behavioral survey because it is relatively easy to design, easy to answer by respondent.
		Distance for ordinal variables is a measure of spatial disorder between two rank / ordering vectors.
		The different between several distances of ordinal variables are based on the type of operations.
	people.revoledu.com /kardi/tutorial/Similarity/OrdinalVariables.html (481 words)

	POWERMUTT: Levels of Measurement (Site not responding. Last check: 2007-09-21)
		Party is, on its face, a pure example of a nominal variable, with the values of the variable being simply the names of the parties (or arbitrary numbers used, for convenience, in place of the names).
		Level of measurement is important because the higher the level of measurement of a variable (note that "level of measurement" is itself an ordinal measure) the more powerful are the statistical techniques that can be used to analyze it.
		Categorical variables generally consist of a small number of values, or categories, and are usually nominal or ordinal.
	www.csupomona.edu /~jlkorey/POWERMUTT/Topics/levels_of_measurement.html (1681 words)

	Ed230B: Ordinal Predictor Variables
		If an ordinal predictor has only three or four levels then clearly it should coded using dummy or effect coding.
		There are times when an ordinal predictor can be treated as if it were interval (this is called quasi-interval) especially if the variable has more than five or six levels.
		Note: Dummy coded variables do not contain significant information that is not contained in the ordinal variable.
	www.gseis.ucla.edu /courses/ed230bc1/notes3/ordinal.html (571 words)

	What is the difference between ordinal, interval and ratio variables? Why should I care?
		A ordinal variable, is one where the order matters but not the difference between values.
		A temperature of 100 degrees C is not twice as hot as 50 degrees C, because temperature C is not a ratio variable.
		A pH of 3 is not twice as acidic as a pH of 6, because pH is not a ratio variable.
	www.graphpad.com /faq/viewfaq.cfm?faq=1089 (617 words)

	Statistics Solutions : Tests for Two Independent Samples
		This set of significance coefficients tests whether an ordinal or interval variable measured in each of two independent samples can be assumed to come from the same underlying population.
		Let n be the size of each of two independent samples A and B, and let the ordinal variable of interest rank subjects from a to k (ex., a measure of "authoritarianism" which ranks subjects from a=1 to k=20).
		Given an ordinal variable which ranks subjects from 1 to k, for each sample separately compute the cumulative percentage of subjects by rank, such that the cumulative percentage of the kth rank will be 100% for each sample.
	www.statisticssolutions.com /mann.htm (1749 words)

	Procedures - MML Ordinal Tables - Details
		The MML ordinal tables procedure was developed to consistently estimate
		This model yields estimates of the mean and variance of the proficiency distribution, the correlation between that distribution and the underlying distribution of x
		The simplest way to do this entails calculating the mean and variance of the (possibly doubly) truncated normal distribution within each cell, given the estimated mean, variance, correlation, and thresholds (see Maddala, 1983 p.
	am.air.org /help/NAEPTextbook/htm/dmmlordinaltables.htm (463 words)

	SmartDrill - Data Mining Datamining
		When the dependent variable we are trying to predict has only two values (e.g., mail responder vs. non-responder), we generate a nominal CHAID model.
		When the dependent variable is at least ordinal (i.e., the values can be arranged in some meaningful order), then we generate an ordinal CHAID model.
		In an ordinal model, each segment is assigned an average value on the dependent variable (e.g., average dollar value), and this is shown in both the tree diagram and the gains chart.
	www.smartdrill.com /About/process4.html (1085 words)

	New Page 1
		Standard deviation: Expresses the degree of variation within a variable on the basis of the average deviation from the mean.
		For dichotomous variables coded between 0 and1 (dummy variables), the mean is useful to indicate the proportions.
		With ordinal variables, the mode, median and range are all useful.
	www.chass.utoronto.ca /~josephf/pol242/LM-2A (760 words)

	Elementary Concepts in Statistics
		Ordinal variables allow us to rank order the items we measure in terms of which has less and which has more of the quality represented by the variable, but still they do not allow us to say "how much more." A typical example of an ordinal variable is the socioeconomic status of families.
		Ratio variables are very similar to interval variables; in addition to all the properties of interval variables, they feature an identifiable absolute zero point, thus they allow for statements such as x is two times more than y.
		It is used only to denote the common variation in the variables in question, that is, the part of variation in one variable that is "explained" by the specific values of the other variable, and vice versa.
	www.statsoft.com /textbook/esc.html (4450 words)

	Mplus Discussion >> Pseudo-R^2 for Models with an Ordinal Response Variable
		The background: In the context of some work I did comparing pseudo-R-squared measures for ordinal response models (e.g., ordinal logit or probit), a reviewer mentioned casually that an alternative to the existing measures could easily be implemented by using polychoric correlations and WLS in an SEM framework, and then somehow obtaining some kind of R-Squared.
		I have data available for a manifest ordinal variable Y, along with a covariate vector of manifest Xs, all continuous or dummies.
		I have categorized Y* into various ordinal Ys, and now wish to compare an SEM- based R-squared to those true values, as well as to the various other existing pseudo-R-squared measures for non-SEM ordinal response models.
	www.statmodel.com /discussion/messages/23/794.html?1125957399 (612 words)

	Chapter 12 answers
		This means that you can use lambda and Yule's Q for ordinal and interval data and gamma or Somers' d for interval or ratio data, although you may have to reduce the number of categories in the ordinal data or convert the continuous interval data to discrete categorical data.
		The education variable is not dichotomous, and it happens to be ordinal, which is good because it is possible to use gamma which requires ordinal data.
		This is not shown by lambda (0.078 vs 0.1046),which is unable to take advantage of the additional information available in the ordinal variable, but it is clearly shown by gamma which does use the extra information (0.5058 for Texas vs. 0.1836 for Alberta).
	www.sfu.ca /~richards/Zen/Pages/Chap12.htm (1800 words)

	Phase 4
		The variable is ordinal—a level one variable refers to not politically/socially active, a level two variable is not very politically/socially active, level three is somewhat active, and four is very active.
		This is a nominal variable; hence, the standard deviation is not useful for determining the validity of the variable: one must use the percent, valid percent, and systems missing information found later in the paper to properly judge the validity.
		The positive value of.060 indicates that the relationship between variables was positive, which supports my thesis, but there was very little strength in the relationship (note: a level 1 is the strongest relationship, while a 0 is the lowest).
	www.msu.edu /user/mitch209/Phase4.htm (2682 words)

	Knodt's Statistical Help
		The variances of the populations are assumed to be homogeneous.
		The levels of the independent variable(s) have been arbitrarily chosen by the researcher and that no generalizations are to be made beyond the levels that are studied.
		The dependent variable is not interval or all the independent variables are not nominal or homoscedasticity cannot be assumed.
	members.aol.com /statware/pubpage.htm (14045 words)

	ORDPLOT: Stata module for cumulative distribution plot of ordinal variable
		ordplot produces a cumulative distribution plot for an ordinal numeric variable ordvar.
		ordplot is designed primarily for data which are, or can be collapsed to, a contingency table with frequencies for an ordinal response and an ordinal or nominal covariate.
		If you experience problems downloading a file, check if you have the proper application to view it first.
	ideas.repec.org /c/boc/bocode/s414301.html (262 words)

	[No title] (Site not responding. Last check: 2007-09-21)
		Example: SES score (Duncan 1961)¡HÅ!jZ!ó0$¨$Combining several ordinal variables ¡%%$¨AExample: Summing Likert scores from several questions related to self-esteem into a single interval measure.
		¡`»»Yªó¨3Scoring ordinal* variables as dichotomous variables ¡44$¨#For independent variables, this means simplifying the ordinal measure with n categories into n-1 dichotomous variables that you then put into the model.
		In a logit, the intercept is the log odds that y = 1. In an ordinal logit, the intercept is the log odds that yi
	www.bsos.umd.edu /socy/smartin/709/709lec060306.ppt (722 words)

Try your search on: Qwika (all wikis)