For each of the following, explain what is wrong and why.
a)
If
b
1
= 5
in a logistic regression analysis with one explanatory variable, we estimate that the probability
of an
event is multiplied by 5 when the value of the explanatory variable increases by one unit.
b) The intercept
b
0
is equal to the odds of an event when
x
= 0
.
c) The odds of an event are 1 minus the probability of the event.
For each of the following, explain what is wrong and why. a) If b 1 =...
12.4 For each of the following, explain what is wrong and why. (a) (1m) A 95% confidence interval for the mean response is the same width regardless of the value of x. (b) (1m) To test H0: b1 = 0, use a t test. (c) (1m) For a particular value of the explanatory variable x, the confidence interval for the mean response will be wider than the prediction interval for a future observation
Suppose we have data on the number of U.S. recruits who were rejected for service in a war against Spain because they did not have enough teeth. We wish to compare the rejection rate for recruits who were under the age of 20 with the rate for those who were 40 or over. To run a logistic regression for this setting, we define an indicator explanatory variable x with values 0 for age under 20 and 1 for age 40...
Suppose we have data on the number of U.S. recruits who were rejected for service in a war against Spain because they did not have enough teeth. We wish to compare the rejection rate for recruits who were under the age of 20 with the rate for those who were 40 or over. To run a logistic regression for this setting, we define an indicator explanatory variable x with values 0 for age under 20 and 1 for age 40...
ApyhoLoaist Conductea) A study o stability (X) and The employees b pe,formaKV) and B stit e The Fite) Response fiaction An employee's emaioha Maxium ik estmas of B D) what is兀estiwatid pelability That emplyees will perform2 Bo and d) use仄likelihaJ Rat tutto determine onterroni obtain a 90% Ghfidene interval fo- Multiple Logistic Regression The LOGISTIC Procedure Model Informatiorn Data Set Response Variable Number of Response Levels2 binary logit Technique Fishers scoring Number of Observations Read Number of Observations Used 27...
Decide (with short explanations) whether the following
statements are true or false.
e) In a simple linear regression model with explanatory variable x and outcome variable y, we have these summary statisties z-10, s/-3 sy-5 and у-20. For a new data point with x = 13, it is possible that the predicted value is y = 26. f A standard multiple regression model with continuous predictors and r2, a categorical predictor T with four values, an interaction between a and...
2.81 What’s wrong? Each of the following statements contains an error. Describe each error and explain why the statement is wrong. A negative relationship is always due to causation. A lurking variable is always a quantitative variable. If the residuals are all negative, this implies that there is a negative relationship between the response variable and the explanatory variable.
6. A study used logistic regression to determine characteristics associated wi th Y wheth er a cancer patient achieved remission (I yes). The most important explanatory variabl was a labeling index (LI) receives an injection of tritiated thymidine. It represents the percentage o "labeled". Results from fitting a logistic regression model using LI to predict π-p 1) are given below: that measures proliferative activity of cells after a patient (Y = Standard Error Constant -3.7771 1.3786 0.1449 0.0593 Parameter Estimate...
1. State whether the following statements are true or false. _1. The value of b in the regression equation is known as the intercept. 2. The more the points are separated in a scatter diagram, the greater the degree of association between the variables. 3. The main reason for expressing the relationship between two variables through a regression equation is to be able to estimate the value of one variable when the value of another is known. 4. The closer...
3. A researcher collected data to study the effect of smoking on the risk of a heart attack. The variables were x - a categorical variable with the categories: (1) Present smoker (2) Past smoker (smoked but quit) (3) Non-smoker Y - a binary variable defined by: Y 1 if the person had a heart attack Y-0 if the person didn't have a heart attack Since the X-variables are categorical, the researcher coded the X-variable by two dummy variables: X2...
2-A-I 1Normall 1 No Spac - EE = :::.:g--. Heading 2- _ Heading 1 Title Paragraph Styles 1: Let us assume that investigators want to examine the effects of soy baby formula on intestinal development. They used 25 baby rats to do the study, and each of them was measured under three different soy percentages (1%, 3.5%, and 5%) What statistical test should they use to test if there is a diference among the average effect of different percentages of...