2023-02-19T06:18:01+03:00[Europe/Moscow] en true <p>Correlation Coefficient</p>, <p>sample</p>, <p>no, but suggests that no linear relationship exists</p>, <p>one or more independent variables( continuous) and a single dependent variable</p>, <p>to establish a relationship between the variables</p>, <p>tell you to the degree of how x influences y</p>, <p>e</p>, <p>OLS</p>, <p>a</p>, <p>b</p>, <p>as we increase the number of times we exercise per month, we increase our life expectancy by 3.45 months. </p>, <p>linearity, homoscedasticity, independence, normality</p>, <p>homoscedasticity</p>, <p>normality</p>, <p>no linear relationship between two variables</p>, <p>constant</p>, <p>to predict a binary outcome variable</p>, <p>a</p>, <p>b</p>, <p>Cox Regression</p>, <p>Cox Regression </p>, <p>smaller hazard in the treatment group that control group</p>, <p>Kaplan-Meier Curve</p>, <p>two curves are equivalent</p>, <p>HR=1</p>, <p>HR&gt;1</p>, <p>HR&lt;1</p> flashcards
Correlation & Regression

Correlation & Regression

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  • Correlation Coefficient

    -provides a measure of how two variables are linearly associated in a sample; providing us with a sense of strength and direction of the relationships between two numerical variables.

  • sample

    R is a ___ statistic.

  • no, but suggests that no linear relationship exists

    What does an R value of 0 zero tell us about two variables? Independent or unrelated?

  • one or more independent variables( continuous) and a single dependent variable

    In a Simple Linear Regression, we have:

  • to establish a relationship between the variables

    What is the goal of regression models?

  • tell you to the degree of how x influences y

    A positive relationship tells you there is a correlation, but does not

  • e

    -is the error of estimate

    -how much variation there is in our estimate of the regression coefficient

  • OLS

    -determines the best-fitting line

    -this line minimizes the sum of segments drawn from the observed data points on the scatter plot to the fitted line.

  • a

    Measures linear association between Y and X.

    a) correlation coefficient

    b) Coefficient of determination

  • b

    Percent change in Y explained by X.

    a) correlation coefficient

    b) Coefficient of determination

  • as we increase the number of times we exercise per month, we increase our life expectancy by 3.45 months.

    This is the equation for the line of best fit regarding the number of times exercised per month to increase in life expectancy. Interpret this data.

    y= 3.45x + 76

  • linearity, homoscedasticity, independence, normality

    What are the assumptions associated with a linear regression model?

  • homoscedasticity

    -one assumes that the error in the relationship between X & Y is distributed equally.

  • normality

    -any fixed value of XY is normally distributed

  • no linear relationship between two variables

    What is the null hypothesis in simple linear regression tests?

  • constant

    -when we have a confounding variable that may influence the outcome of one group over the other.

    -we have to make that variable constant

    ex: age & blood pressure + antihypertensive medication use

  • to predict a binary outcome variable

    When do we use a logistic regression?

  • a

    OR>1 indicates:

    a) odds of having event increases as predictor increases

    b) odds of having the event decreases as the predictor increases

  • b

    OR < 1 indicates:

    a) odds of having event increases as predictor increases

    b) odds of having the event decreases as the predictor increases

  • Cox Regression

    -outcome of interest consists of the occurrence and timing of an event

    ex: cardiac event, mortality, relapse, the onset of disease

  • Cox Regression

    What test do we use when we follow subjects over time from a well-defined time point?

  • smaller hazard in the treatment group that control group

    HR < 1 indicates what?

  • Kaplan-Meier Curve

    estimates survival curves for:

    - a proportion of the sample (50%)

    -probability up to and beyond a given time

    -compares survival among groups

  • two curves are equivalent

    What is the null hypothesis for Kaplan-Meier Curves?

  • HR=1

    No relationship

  • HR>1

    Greater hazard in the treatment group than in the control group

  • HR<1

    Smaller hazard in the treatment group than in the control group