PQStat - Baza Wiedzy en:statpqpl:wielowympl

ANCOVA

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T21:27:33+00:00

ANCOVA Analysis of covariance (ANCOVA) is a method of testing the hypothesis that the means of two or more populations are equal, in correction for other continuous variables. These adjustments result in effects more readily seen by researchers than those obtained through ANOVA, i.e., narrower confidence intervals and greater statistical power. Suppose an experiment is conducted to evaluate the effects of two treatments. The groups randomly assigned to treatment differ slightly in mean age, whi…

Factorial ANOVA - GLM

Anonymous (anonymous@undisclosed.example.com) — 2022-02-09T16:26:25+00:00

Factorial ANOVA - GLM Okno z ustawieniami opcji ANOVA czynnikowa GLM wywołujemy poprzez menu Statystyka→Modele wielowymiarowe→ANOVA czynnikowa GLM Czynnikowa analiza wariancji GLM jest rozszerzeniem jednoczynnikowej analizy wariancji (ANOVA) dla grup niezależnych oraz liniowej regresji wielorakiej. Skrót GLM (ang. general linear model) czytamy jako Ogólny Model Liniowy. Analiza GLM polega zwykle na wykorzystaniu modeli regresji li…

Comparison of logistic regression models

Anonymous (anonymous@undisclosed.example.com) — 2022-11-19T18:33:29+00:00

Comparison of logistic regression models The window with settings for model comparison is accessed via the menu Advanced Statistics→Multivariate models→Logistic regression -- comparing models Due to the possibility of simultaneous analysis of many independent variables in one logistic regression model, similarly to the case of multiple linear regression, there is a problem of selection of an optimum model. When choosing independent variables one has to remember to put into the model variable…

Logistic regression

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T18:58:04+00:00

Logistic regression The window with settings for Logistic Regression is accessed via the menu Advanced statistics→Multidimensional Models→Logistic Regression The constructed model of logistic regression (similarly to the case of multiple linear regression) allows the study of the effect of many independent variables (

Mediation effect

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T19:21:30+00:00

Mediation effect Baron and Kenny (1986) defined a mediator (M) as a variable that significantly explains the relationship between the independent variable (X) and the outcome variable (Y). In mediation, the relationship between the independent variable and the dependent variable is assumed to be an indirect effect that exists due to the influence of a third variable (mediator).

Comparison of multiple linear regression models

Anonymous (anonymous@undisclosed.example.com) — 2022-11-19T18:10:21+00:00

Comparison of multiple linear regression models The window with settings for model comparison is accessed via the menu Advenced statistics→Multidimensional models→Multiple regression -- model comparison The multiple linear regression offers the possibility of simultaneous analysis of many independent variables. There appears, then, the problem of choosing the optimum model. Too large a model involves a plethora of information in which the important ones may get lost. Too small a model involv…

Preparation of variables for analysis

Anonymous (anonymous@undisclosed.example.com) — 2022-02-26T15:36:34+00:00

Preparation of variables for analysis Matching groups Why is group matching done? There are many answers to this question. Let us use an example of a medical situation. If we estimate the treatment effect from a fully randomized experiment

Multiple Linear Regression

Anonymous (anonymous@undisclosed.example.com) — 2023-03-31T19:10:36+00:00

Multiple Linear Regression The window with settings for Multiple Regression is accessed via the menu Advanced statistics→Multidimensional Models→Multiple Regression The constructed model of linear regression allows the study of the influence of many independent variables(