Dummy variable (statistics) (original) (raw)
Als Dummy-Variable (auch Designvariable, Indikatorvariable, boolesche Variable, Stellvertreter-Variable oder selten Scheinvariable; englisch dummy variable) bezeichnet man in der statistischen Datenanalyse eine Variable mit den Ausprägungen 1 und 0 (ja-nein-Variable), die als Indikator für das Vorhandensein einer Ausprägung einer mehrstufigen Variablen dient. Diese der Dummy-Variable zugrunde liegende Variable kann ein beliebiges Skalenniveau haben.
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| dbo:abstract | Als Dummy-Variable (auch Designvariable, Indikatorvariable, boolesche Variable, Stellvertreter-Variable oder selten Scheinvariable; englisch dummy variable) bezeichnet man in der statistischen Datenanalyse eine Variable mit den Ausprägungen 1 und 0 (ja-nein-Variable), die als Indikator für das Vorhandensein einer Ausprägung einer mehrstufigen Variablen dient. Diese der Dummy-Variable zugrunde liegende Variable kann ein beliebiges Skalenniveau haben. (de) In regression analysis, a dummy variable (also known as indicator variable or just dummy) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. For example, if we were studying the relationship between gender and income, we could use a dummy variable to represent the gender of each individual in the study. The variable would take on a value of 1 for males and 0 for females. Dummy variables are commonly used in regression analysis to represent categorical variables that have more than two levels, such as education level or occupation. In this case, multiple dummy variables would be created to represent each level of the variable, and only one dummy variable would take on a value of 1 for each observation. Dummy variables are useful because they allow us to include categorical variables in our analysis, which would otherwise be difficult to include due to their non-numeric nature. They can also help us to control for confounding factors and improve the validity of our results. As with any addition of variables to a model, the addition of dummy variables will increases the within-sample model fit (coefficient of determination), but at a cost of fewer degrees of freedom and loss of generality of the model (out of sample model fit). Too many dummy variables result in a model that does not provide any general conclusions. Dummy variables are useful in various cases. For example, in econometric time series analysis, dummy variables may be used to indicate the occurrence of wars, or major strikes. It could thus be thought of as a truth value represented as a numerical value 0 or 1 (as is sometimes done in computer programming). Dummy variables may be extended to more complex cases. For example, seasonal effects may be captured by creating dummy variables for each of the seasons: D1=1 if the observation is for summer, and equals zero otherwise; D2=1 if and only if autumn, otherwise equals zero; D3=1 if and only if winter, otherwise equals zero; and D4=1 if and only if spring, otherwise equals zero. In the panel data fixed effects estimator dummies are created for each of the units in cross-sectional data (e.g. firms or countries) or periods in a . However in such regressions either the constant term has to be removed, or one of the dummies removed making this the base category against which the others are assessed, for the following reason: If dummy variables for all categories were included, their sum would equal 1 for all observations, which is identical to and hence perfectly correlated with the vector-of-ones variable whose coefficient is the constant term; if the vector-of-ones variable were also present, this would result in perfect multicollinearity, so that the matrix inversion in the estimation algorithm would be impossible. This is referred to as the dummy variable trap. (en) Athróg a úsáidtear san anailís cúlaithe is ea athróg chaoch, a rangaítear mar náid nó mar aon, mar athróg chineálach. (ga) In econometria, una variabile binaria, o variabile dummy, è una variabile che assume valore 0 o 1, a seconda che sia soddisfatta o meno una data condizione. È inserita in una regressione multivariata con lo scopo di catturare l'effetto di una variabile qualitativa sul valore medio della variabile dipendente, andando a modificare l'intercetta; in tal senso permette di migliorare l'adattamento della regressione, poiché consente di cogliere ed inserire nel sistema di variabili anche fattori extrastatistici.È inoltre talvolta utilizzata al fine di anestetizzare l'effetto distorsivo di una variabile endogena del sistema che presenta una o più osservazioni anomale; in tal caso, assume la forma di un vettore con valori tutti uguali a 0 (zero), ad esclusione di quello corrispondente all'osservazione anomala che si intende eliminare. L'utilizzo delle variabili binarie risulta estremamente profittevole di fronte a regressioni multivariate di fenomeni economici con osservazioni protratte nel tempo. Per fare un esempio, volendo costruire una regressione che descriva (variabile esogena) l'andamento del commercio tra paesi europei (si utilizzano di norma variabili ponderate sui valori di import ed export), troveremmo una o più variazioni positive in corrispondenza dei valori successivi all'entrata in vigore dei vari accordi commerciali. Tali osservazioni inficierebbero in modo negativo sull'adattamento della regressione, ossia sulla capacità delle variabili selezionate di "spiegare" il fenomeno oggetto di analisi. Per ovviare a questo difetto, si possono inserire una o più dummy, variabili vettori con elementi tutti nulli ad eccezione di quelli corrispondenti alle osservazioni shiftate. (it) 가변수(Dummy variable, 假變數)란 독립변수를 0과1로 변환한 변수를 의미한다. 일반적인 경우 그 사실 여부에 대해 예/아니오로 확인 가능한 질적 변수(예: 남자인가? 대학교를 졸업했는가?)는 회귀 분석에 직접 투입하는 것이 불가능하다. 이러한 질적 변수를 회귀분석에 사용하기 위해 그 가부를 0 혹은 1 의 숫자 형태로 대응시킨 변수를 가변수라 한다. 경제학에서 가장 흔하게 언급되는 가변수의 용례 로는 '성별에 따른 월급격차'로, 다음과 같은 형태가 된다. (ko) Dummy coding – w statystyce jest to metoda kodowania danych nominalnych (jakościowych) na dane liczbowe przyjmujące wartości 0 i 1 w celu ich analizy statystycznej. Przykład zastosowania: związek między płcią (wartości: kobieta i mężczyzna) a trybem studiów (wartości: stacjonarne i niestacjonarne) możemy obliczyć za pomocą wzoru na współczynnik fi. Można jednak osiągnąć ten sam efekt (czyli obliczyć siłę związku pomiędzy płcią i trybem studiów) za pomocą współczynnika korelacji liniowej Pearsona, jednak wcześnie trzeba zastosować dummy coding. Zmienną płeć rekodujemy na dane liczbowe: wartość kobieta jest rekodowana na 0, wartość mężczyzna na 1. To samo robimy ze zmienną tryb studiów: wartość stacjonarne rekodujemy na 0, wartość niestacjonarne rekodujemy na 1. (pl) 虚拟变量（英語：dummy variable），又稱哑变量，指在统计学和计量经济学，尤其是迴歸分析中僅取0或1的值，以此表示某些可能改变结果的定性效应之有无的变量。可以认为，虚拟变量是回归模型中用数字来替代并表示定性事实，从而将数据分为互斥的类别（如吸烟者及非吸烟者）。 虚拟自变量（又称虚拟解释变量）取值为0时，该变量的系数对因变量没有影响，而当虚拟变量取值为1时，其系数会改变截距。例如，假定某人是否为某组的成员是与回归相关的定性变量之一，如果属于该组成员以1代表，则其他所有人获得0值，此时截距对非成员是常数项，对成员则是常数项加上“成员”虚拟变量的系数。 虚拟变量常用于时间序列分析，包括状态转换、季节性分析和定性数据应用。 (zh) Фиктивная переменная (англ. dummy variable) — качественная переменная, принимающая значения 0 и 1, включаемая в эконометрическую модель для учёта влияния качественных признаков и событий на объясняемую переменную. При этом фиктивные переменные позволяют учесть влияние не только качественных признаков, принимающих два значения, но и несколько возможных. В этом случае добавляются несколько фиктивных переменных. Фиктивная переменная может быть также индикатором принадлежности наблюдения к некоторой подвыборке. Последнее можно использовать для обнаружения структурных изменений. (ru) |
| dbo:wikiPageExternalLink | http://hspm.sph.sc.edu/courses/J716/pdf/716-6%20Dummy%20Variables%20and%20Time%20Series.pdf https://web.archive.org/web/20060301032127/http:/hspm.sph.sc.edu/courses/J716/pdf/716-6%20Dummy%20Variables%20and%20Time%20Series.pdf https://web.archive.org/web/20111216051820/https:/stat.ethz.ch/~maathuis/teaching/stat423/handouts/Chapter7.pdf http://stat.ethz.ch/~maathuis/teaching/stat423/handouts/Chapter7.pdf https://socialsciences.mcmaster.ca/jfox/Courses/SPIDA/dummy-regression-notes.pdf |
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| rdfs:comment | Als Dummy-Variable (auch Designvariable, Indikatorvariable, boolesche Variable, Stellvertreter-Variable oder selten Scheinvariable; englisch dummy variable) bezeichnet man in der statistischen Datenanalyse eine Variable mit den Ausprägungen 1 und 0 (ja-nein-Variable), die als Indikator für das Vorhandensein einer Ausprägung einer mehrstufigen Variablen dient. Diese der Dummy-Variable zugrunde liegende Variable kann ein beliebiges Skalenniveau haben. (de) Athróg a úsáidtear san anailís cúlaithe is ea athróg chaoch, a rangaítear mar náid nó mar aon, mar athróg chineálach. (ga) 가변수(Dummy variable, 假變數)란 독립변수를 0과1로 변환한 변수를 의미한다. 일반적인 경우 그 사실 여부에 대해 예/아니오로 확인 가능한 질적 변수(예: 남자인가? 대학교를 졸업했는가?)는 회귀 분석에 직접 투입하는 것이 불가능하다. 이러한 질적 변수를 회귀분석에 사용하기 위해 그 가부를 0 혹은 1 의 숫자 형태로 대응시킨 변수를 가변수라 한다. 경제학에서 가장 흔하게 언급되는 가변수의 용례 로는 '성별에 따른 월급격차'로, 다음과 같은 형태가 된다. (ko) Dummy coding – w statystyce jest to metoda kodowania danych nominalnych (jakościowych) na dane liczbowe przyjmujące wartości 0 i 1 w celu ich analizy statystycznej. Przykład zastosowania: związek między płcią (wartości: kobieta i mężczyzna) a trybem studiów (wartości: stacjonarne i niestacjonarne) możemy obliczyć za pomocą wzoru na współczynnik fi. Można jednak osiągnąć ten sam efekt (czyli obliczyć siłę związku pomiędzy płcią i trybem studiów) za pomocą współczynnika korelacji liniowej Pearsona, jednak wcześnie trzeba zastosować dummy coding. Zmienną płeć rekodujemy na dane liczbowe: wartość kobieta jest rekodowana na 0, wartość mężczyzna na 1. To samo robimy ze zmienną tryb studiów: wartość stacjonarne rekodujemy na 0, wartość niestacjonarne rekodujemy na 1. (pl) 虚拟变量（英語：dummy variable），又稱哑变量，指在统计学和计量经济学，尤其是迴歸分析中僅取0或1的值，以此表示某些可能改变结果的定性效应之有无的变量。可以认为，虚拟变量是回归模型中用数字来替代并表示定性事实，从而将数据分为互斥的类别（如吸烟者及非吸烟者）。 虚拟自变量（又称虚拟解释变量）取值为0时，该变量的系数对因变量没有影响，而当虚拟变量取值为1时，其系数会改变截距。例如，假定某人是否为某组的成员是与回归相关的定性变量之一，如果属于该组成员以1代表，则其他所有人获得0值，此时截距对非成员是常数项，对成员则是常数项加上“成员”虚拟变量的系数。 虚拟变量常用于时间序列分析，包括状态转换、季节性分析和定性数据应用。 (zh) Фиктивная переменная (англ. dummy variable) — качественная переменная, принимающая значения 0 и 1, включаемая в эконометрическую модель для учёта влияния качественных признаков и событий на объясняемую переменную. При этом фиктивные переменные позволяют учесть влияние не только качественных признаков, принимающих два значения, но и несколько возможных. В этом случае добавляются несколько фиктивных переменных. Фиктивная переменная может быть также индикатором принадлежности наблюдения к некоторой подвыборке. Последнее можно использовать для обнаружения структурных изменений. (ru) In regression analysis, a dummy variable (also known as indicator variable or just dummy) is one that takes the values 0 or 1 to indicate the absence or presence of some categorical effect that may be expected to shift the outcome. For example, if we were studying the relationship between gender and income, we could use a dummy variable to represent the gender of each individual in the study. The variable would take on a value of 1 for males and 0 for females. (en) In econometria, una variabile binaria, o variabile dummy, è una variabile che assume valore 0 o 1, a seconda che sia soddisfatta o meno una data condizione. È inserita in una regressione multivariata con lo scopo di catturare l'effetto di una variabile qualitativa sul valore medio della variabile dipendente, andando a modificare l'intercetta; in tal senso permette di migliorare l'adattamento della regressione, poiché consente di cogliere ed inserire nel sistema di variabili anche fattori extrastatistici.È inoltre talvolta utilizzata al fine di anestetizzare l'effetto distorsivo di una variabile endogena del sistema che presenta una o più osservazioni anomale; in tal caso, assume la forma di un vettore con valori tutti uguali a 0 (zero), ad esclusione di quello corrispondente all'osservazio (it) |
| rdfs:label | Dummy-Variable (de) Dummy variable (statistics) (en) Athróg chaoch (ga) Variabile di comodo (it) 가변수 (ko) Dummy coding (pl) Фиктивная переменная (ru) 虚拟变量 (zh) |
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