Simple/Multiple linear regression - Austin - IPP 3 Exam 2

Match the following definitions with their

• Bias

• A statistical method that allows you to examine the relationship between two or more variables of interest

• Regression Analysis

• Situations in which researchers must accept that some of or all of the design without modification

• Confounder

• Any factor that prevents appropriate statistical interpretation of a results within practical context of a study

• Variable control

• When not maintained properly leads to bias. controlling for one variable while we change another

• Nature experiments

• A form of error. statistical terms/values that do not provide an accurate representation of the population

Match the following definitions with their descriptions

• Omitted Variable

• Any variable that produces a modifying effect

• Effect Modification

• A specific and observable factor that is omitted from the analysis

• Biased Samples

• Fundamentally different estimates then the population parameter

• Inefficient

• The unadjusted results when adjustments lead to changes in any estimate of variation

• Confounding effect

• A variable that, when accounted for, leads to a meaningfully different interpretation of relationship between the primary and independent variables and the dependent variables

Match the following definitions with their descriptions

• Unbiased Sample

• Statistical adjustments for the cofounder result in

• R²

• A value between 0 and 1. As it approaches 0 regression explains very little variation in y. As it approaches 1 it explains it well.

• Ordinary least squares (OLS)

• A intermediate between the primary independent variable and the dependent variable that can be used to analyze a relationship

• Mediating Effect

• Vertical relationship between each data point and trendline

• Residual

• Simplest process of estimation which assumes dependent variable is continous

An R² close to 0 indicates a strong correlation and linear relationship

• True

• False

Both confounding variables and/or omitted variables can lead to bias

• True

• False

For which of the following types of data would you use dummy variables?

• Patients height

• Time spent drinking coffee

• Hours spent traveling

• Visited another country

You design a study to determine if the numbers of hours watching scrubs correlates to the grade range achieved in IPP3. You also consider other factors such as location, video speed used, and average time snacking. Which of the following is the independent variable

• Number of hours watching scrubs

• Time snacking

• Video speed used

• Grade acheived

You design a study to determine if the numbers of hours watching scrubs correlates to the grade range achieved in IPP3. You also consider other factors such as location, video speed used, and average time snacking. Number of hours watching scrubs would be which of the following

• Confounding effect

• Effect modulator

• Mediating effect

• None of the above

You design a study to determine if the numbers of hours watching scrubs correlates to the grade range achieved in IPP3. You also consider other factors such as location, video speed used, and average time snacking. Video speed would be which of the following

• Confounding effect

• Effect moderator

• Mediating effect

• None of the above

You design a study to determine if the numbers of hours watching scrubs correlates to the grade range achieved in IPP3. You also consider other factors such as location, video speed used, and average time snacking. How would you conduct this study?

• Simple regression

• Multiple regression

• Logistical regression

• Survival analysis