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Topic: Lurking Variable

	Lurking variable - Wikipedia, the free encyclopedia
		A lurking variable (confounding factor or variable, or simply a confound or confounder) is a "hidden" variable in a statistical or research model that affects the variables in question but is not known or acknowledged, and thus (potentially) distorts the resulting data.
		This hidden third variable causes the two measured variables to falsely appear to be in a causal relation.
		In statistical experimental design, attempts are made to remove lurking variables such as the placebo effect from the experiment.
	en.wikipedia.org /wiki/Confounding (379 words)

	FAQ Statistics (Site not responding. Last check: 2007-11-03)
		Answer: A confounding variable is a special case of a lurking variable.
		Lurking variables can also be responsible for a common response.
		The standard deviation of a random variable is a theoretical quantity which is computed with the formula on page 336.
	www.georgetown.edu /faculty/engler/Statistics/FAQ.html (2595 words)

	Stats Glossary (Site not responding. Last check: 2007-11-03)
		The response variable is affected or predicted by the explanatory variable.
		Generally, the response variable is on the vertical axis and the explanatory variable is on the horizontal axis.
		Often, if two variables are associated but a cause-and-effect relationship is not apparent, then it is likely the case that the two variables are related to a third variable that is not being measured.
	www.westga.edu /~abarlow/math_4713_stats_glossary.html (2429 words)

	ED230B/C: Variance & Covariance
		The squared value represents the proportion of variance of one variace that is shared with the other variable, in other words, the proportion of the variance of one variable that can be predicted from the other variable.
		Often a third variable, a lurking variable, that is not included in the analysis is responsible (causes) for the first two variables.
		It represents the proportion of variability of a that is accounted for by the combination of b, c, and d.
	www.gseis.ucla.edu /courses/ed230bc1/notes1/var1.html (716 words)

	The sample correlation coefficient between annual raises and teaching evaluations for a sample of 353 college faculty ...
		A variable that is not among the variables studied but that affects the response variable.
		Confounding means that the effect of the explanatory variable on the response variable can't be separated from the effect of other variables on the response.
		Strong correlation between two variables is evidence of a cause and effect relationship between the variables.
	www-rohan.sdsu.edu /~hnoble/stat250ex1areview.htm (1042 words)

	Chapter 4: Sample Surveys in the Real World
		Lurking variable - a variable that has an important effect on the relationship among the variables in a study but is not one of the explanatory variables being studied.
		Another type of confounding is the lurking variable that people tend to respond differently when they know they are being studied.
		Hence, we are controlling the effects of lurking variables on the response.
	www.ms.uky.edu /~griffith/STA200_5.htm (904 words)

	[No title]
		Lurking Variable: A variable that is not among the explanatory or response variables in a study yet may influence the interpretation of relationships among those variables.
		Confounding: Two variables are confounded when their effects on a response variable cannot be distinguished from each other.
		The confounded variables may be either explanatory variables or lurking variables.
	www.stat.purdue.edu /~jkbrenne/stat301/notes.sec.2.5.doc (397 words)

	Math words page 19 (via CobWeb/3.1 planetlab2.cs.unc.edu) (Site not responding. Last check: 2007-11-03)
		Various symbols are still in use for the determinant, with the most common being a set of vertical lines similar to the absolute value,A, or the abbreviation det(A), where A is the name of the matirix.
		A. From Joiner, ``Lurking variables: some examples,'' American Statistician 35 (1981): ``A lurking variable is, by definition, a variable that has an important effect and yet is not included among the predictor variables under consideration.'' Joiner attributes the term to George Box.
		This isn't a well-defined technical term, and I prefer to expand the Box/Joiner idea a bit: A lurking variable is a variable that is not among the explanatory or response variables in a study, and yet may (or may not) influence the interpretation of relationships among those variables.
	www.pballew.net.cob-web.org:8888 /arithm19.html (5037 words)

	Linear Regression (via CobWeb/3.1 planetlab2.cs.unc.edu) (Site not responding. Last check: 2007-11-03)
		A valuable numerical measure of association between two variables is the correlation coefficient, which is a value between -1 and 1 indicating the strength of the association of the observed data for the two variables.
		A lurking variable exists when the relationship between two variables is significantly affected by the presence of a third variable which has not been included in the modeling effort.
		Since such a variable might be a factor of time (for example, the effect of political or economic cycles), a time series plot of the data is often a useful tool in identifying the presence of lurking variables.
	www.stat.yale.edu.cob-web.org:8888 /Courses/1997-98/101/linreg.htm (1057 words)

	ED230A Measuring Association
		Scatterplots are used to plot two variables simultaneously, i.e., the joint distribution (also called a bivariate distribution) of two variables.
		Scatterplots that appear as a random circular cluster of points indicate low associations between the variables and would be said to have a a low degree of correlation (correlation close to zero).
		The squared value represents the proportion of variance of one variable that is shared with the other variable, in other words, the proportion of the variance of one variable that can be predicted from the other variable.
	www.gseis.ucla.edu /courses/ed230a2/notes/cor1.html (494 words)

	[No title]
		Lurking Variable A lurking variable is a variable that is not among the explanatory or response variables in a study and yet may influence the interpretation of relationships among those variables.
		The observed association between the variables x and y is explained by a lurking variable z.
		Lurking variables may also cause confounding, in which case both the explanatory variable and the lurking variables cause changes in the response, but we cannot distinguish their individual effects.
	cda.mrs.umn.edu /~jongmink/STAT1601/Chapter2.45.doc (1350 words)

	Chapter 4 (Site not responding. Last check: 2007-11-03)
		A) a variable that is not among the variables studied but that affects the response variable.
		C) association is due to the presence of a lurking variable (major league teams tend to be in large cities with more people, hence a greater number of divorces).
		8. If changes in a response variable are due to the effects of the explanatory variable as well as the effects of lurking variables, and we cannot distinguish between these effects, we are said to have
	4dw.net /bgoforth/ap4.htm (704 words)

	Experimental Design
		It is the dependent variable in the study.
		is one that has an effect on relationships among the identified variables in a study but is not itself included among those variables studied.
		the effects of lurking variables on the response by establishing comparative treatments (usually using a placebo).
	www.warren-wilson.edu /~teller/courses/mat141/exp_dsgn.htm (465 words)

	Scatterplots
		Usually the response variable is plotted along the vertical axis and the explanatory variables is plotted along the horizontal axis.
		A lurking variable is a third variable that is related to both variables and may confound the association.
		Sometimes the lurking variable is a 'grouping' variable of sort.
	www.math.sfu.ca /~cschwarz/Stat-301/Handouts/node39.html (625 words)

	[No title]
		A variable is described as lurking if it has an important effect on the relationship among the variables in a study but is not included among the variables actually measured in the study.
		Two variables (either explanatory or lurking variables) are confounding when their effects on a response variable cannot be distinguished from each other.
		Identify the experimental units, response variable, the factors, levels, and treatments in a single- or multi-factor experiment.
	www.etsu.edu /math/hosler/Ch78_F04.doc (1388 words)

	SkyTonight.com - Variable Stars (Site not responding. Last check: 2007-11-03)
		It's one of the brightest such variables to begin with (typically peaking at about magnitude 5.2), but in late July and early August 2006, it peaked at about magnitude 3.8.
		This red long-period variable is sometimes visible to the unaided eye — and sometimes invisible even in a 4-inch telescope.
		Lurking in the seemingly changeless constellations are a few inconstant stars that pulse and eclipse.
	skytonight.com /observing/objects/variablestars (240 words)

	Measuring Usability: Analyzing Task Times
		One lurking variable when analyzing task times is the user's tendency to perform better on the later tasks and worse on the earlier tasks.
		If we wanted to compare the variation for all tasks we would need a way to control for the difference in tasks times.
		For example, one task might have a mean time of 200 seconds and a standard deviation of 30 seconds whereas another task may have a mean time of 30 seconds and standard deviation of 8 seconds.
	www.measuringusability.com /random.htm (570 words)

	lect1120
		Residuals, plotted against the original X variable are supposed to show no clear pattern and should look like a random scattering of points.
		A confounder (or a lurking variable) is a variable that has an important effect on the relationship between two variables -- but for whatever reason -- it is not being studied.
		Finding a lurking variable is more of an "art" than a science.
	www.stat.ucla.edu /~vlew/stat11/WI01/old/lectures/lect1120.html (846 words)

	R: Lurking variable plot (via CobWeb/3.1 planetlab2.cs.unc.edu) (Site not responding. Last check: 2007-11-03)
		This function generates a `lurking variable' plot for a fitted point process model.
		The correct form (of the spatial trend part of the model) may be suggested by the shape of the plot.
		Note that lurking variable plots for the x and y coordinates are also generated by
	www.maths.lth.se.cob-web.org:8888 /help/R/.R/library/spatstat/html/lurking.html (783 words)

	SPURIOUS CORRELATION (Site not responding. Last check: 2007-11-03)
		Spurious Relation (or Correlation) (a) - A situation in which measures of two or more variables are statistically related (they cover) but are not in fact causally linked—usually because the statistical relation is caused by a third variable.
		When the effects of the third variable is taken into account, the relationship between the first and second variable disappears.
		A lurking variable is a source of a spurious correlation.
	www.autobox.com /spur2.html (155 words)

	[No title]
		(a) Before plotting the scatterplot, decide which of the variables year and time would be the response variable and which would be the predictor variable.
		Lurking Variables The relationship between two variables may be influenced by other variables.
		A lurking variable is an unobserved variable having an important effect on the relationship among the variables in a study.
	statweb.calpoly.edu /ccast/Regression-Olympics.doc (476 words)

	Spurious Correlations (Site not responding. Last check: 2007-11-03)
		Thus the variables that are available for analysis are not necessarily the ones that would be chosen as the ideal set of variables given the purposes of the analysis.
		For example, suppose that the critical variable is correlated with race, age, or gender.
		Cases involving third variables typically apply to correlational studies, procedural bias to experimental studies, and impurities to both types of studies.
	www.burns.com /wcbspurcorl.htm (2910 words)

	Exam 1 Review
		Lurking variable is responsible for both explanatory and response values
		Explanatory and lurking variables may work together to affect the response (see Examples 2.34, p.
		Lurking variable may work in opposite direction of explanatory variable, making the association appear in the opposite direction of the actual cause-and-effect relationship between explanatory and response variables (see Exercise 2.94, p.
	www.calvin.edu /~scofield/courses/m143/materials/review/e1S04.shtml (635 words)

	Statistics (Site not responding. Last check: 2007-11-03)
		variable(s) that influence but are not a part of the study
		the variable that is expected to give a certain response
		occurs when a lurking variable interferes with the study
	www.hutchcc.edu /faculty/turnerp/StatsQuiz7.htm (220 words)

	Simpson's paradox - Wikipedia, the free encyclopedia
		In this example the lurking variable (or confounding variable) of stone size was not previously known to be important until its effects were included.
		The "lurking variable" principle also works with the Electoral College, which determines the winner of United States presidential elections.
		The lurking variable is the differing number of electoral votes each state carries.
	en.wikipedia.org /wiki/Simpson's_paradox (1155 words)

	Lurking Variables (Site not responding. Last check: 2007-11-03)
		A lurking variable is a variable that has an important effect on the relationship among the variables in a study but is not included among the variables studied.
		Harder tires present less rolling resistance and improve gas mileage; therefore, the Buick Estate Wagon outperformed our expectations based on our regression model, which did not account for tire inflation pressure.
		In our model Tire Pressure is a lurking variable, variable that seems to help in predicting gas mileage but is not included in the model.
	score.kings.k12.ca.us /lessons/wwwstats/lurking.variables.html (480 words)

	Conditional Probability and Independence: Basics 3
		is a variable which has an important effect on outcomes, but which has not been accounted for in the data.
		The condition of the patient is a lurking variable.
		When data are aggregated over a lurking variable, the results may reverse.
	www.metamath.com /webstat/B-3/basics3.html (199 words)

	AP Stat Quiz on Chapter 2
		A researcher is interested in determining if one could predict the score on a statistics exam from the amount of time spent studying for the exam.
		The researcher must have made a mistake since these two variables are clearly unrelated and must have correlation 0.
		Suppose the correlation between two variables x and y is due to the fact that both are responding to changes in some unobserved third variable.
	www.ktb.net /~cct/stat/StatCh2.html (1282 words)

	[No title]
		Other possible answers might be variations on this idea; for example, if we believe that success in college depends on a student’s self-confidence, we might suppose that confident students are more likely to choose math courses.
		2.64) The explanatory and response variables were “consumption of herbal tea” and “cheerfulness/health.” The most important variable is social interaction; many of the nursing home residents may have been lonely before the students started visiting.
		2.66) Social status is a possible lurking variable: Children from upper-class families can more easily afford higher education, and they would typically have had better preparation for college as well.
	www.math.unl.edu /~kwong/homework/H7.doc (731 words)

	Exam 3 Review
		Explanatory variable (if there is one) should be on horizontal axis, response variable on vertical
		Purpose: to determine if the data values for that quantitative variable appear to be normally distributed (determined by whether or not the plot appears linear)
		Scenarios/types of questions for which such an approach is possible (response variable is reduced to two values: yes or no, success or failure)
	www.calvin.edu /~scofield/courses/m143/materials/review/e3S01.shtml (885 words)

	[No title]
		The regression method uses the correlation to approximate the average value of the Y variable at a given X. The regression equation is a formula for doing this.
		If the variance of the residuals is small, then the average deviation from the regression line is small.
		If there is an association between a categorical variable and the lurking variable then there is an opportunity for a reversal.
	www-stat.wharton.upenn.edu /~pzhang/stat101/Lecture5.doc (2029 words)

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