Home » Fitting Statistical Models to Data with Python » Suppose that the migraine researcher was also interested in pain score trends immediately following administration of the drug. The researcher continues to collect pain score measurements at four, six, and eight hours after administration of either the experimental drug or the placebo pill.

Suppose that the migraine researcher was also interested in pain score trends immediately following administration of the drug. The researcher continues to collect pain score measurements at four, six, and eight hours after administration of either the experimental drug or the placebo pill.

Question 3

Suppose that the migraine researcher was also interested in pain score trends immediately following administration of the drug. The researcher continues to collect pain score measurements at four, six, and eight hours after administration of either the experimental drug or the placebo pill. The researcher wants to then model the pain score as a function of the previously mentioned variables in addition to time since administration.

What needs to change about the model that the researcher is now fitting?

1 / 1 point

The correlation of the repeated measures needs to be taken into account, and time since administration needs to be added to the model as an independent variable.

The correlation of the repeated measures needs to be taken into account, but nothing else needs to be change

Nothing; the same model mentioned in Problem 2 will be appropriate for studying the group differences.

Time needs to be added to the model as an independent variable; nothing else needs to be changed.

Time needs to be added to the model as a dependent variable; nothing else needs to be changed.

A researcher at a large pharmaceutical company wishes to study the effect of a new experimental drug on the amount of pain suffered by people who frequently experience migraines. The researcher…

After performing the analysis, the researcher writes a press release describing the results of the experiment, and claims that the new experimental drug will reduce pain by 25% based on the results of…

Which of the following scatterplot(s) would fitting a linear regression model to the data be appropriate? (Select all that apply.)

NHANES records whether an individual has smoked 100 cigarettes or more. The next few questions will focus on fitting models to predict whether someone has smoked 100+ cigarettes. First, a model is fit…

Background for Questions 7 - 13 In 1905, R.J. Gladstone conducted a study of the relationship between brain weight and size of the head. Brain weight (grams) and head size (cubic cm) measurements were…

You are interested in estimating the relationship between gender (the IV) and a binary indicator of ever having experienced a major depressive disorder (the DV), where both variables were collected…

You are interested in predicting the probability that an NCAA men's basketball team wins their first round game in the annual NCAA men's basketball tournament, where potential predictors of the binary…

You wish to fit a model to a "forced choice" binary dependent variable measuring political party preference (if you had to pick a political party, which would you select: Democratic or Republican?),…

Imagine that you are collecting variables while participants attempted to shoot a soccer ball. Which of the following collected variables could be predicted using a logistic regression model?

A new model was fit, this time adding in the two categorical variables Sex (0=male, 1=female) and Age (0=young, 20-46 years old, 1= old, 46+ years old), the model summary is shown below

Which of the following scatterplot(s) would have a correlation coefficient that is close to 0? (Select all that apply.)

Which of the following scatterplots would have the highest absolute correlation (i.e. shows the strongest linear relationship?

Which of the following features has the highest correlation between two observations in the same cluster?

What most likely happened to our R-Squared value when we added the third predictor LSTAT to our initial model?

We’d like to predict the log odds of smoking 100+ cigarettes for a given individual using the logistic regression model with the two variables: BMI and Age. For an individual with a BMI of 22 who is…