Questions and Answers of Inferential Statistics

Repeat the analysis of Problem 14.9 using the data in Table D-49, Appendix D. Compare this result to that of Problem 14.9. Fully explain your answer.
Repeat the analysis of Problem 14.8 for the dependent variable F, using starting values b1 = 5, b2 = 1.6, b3 = 300, and b4 = .05. Then repeat starting from b3 = 200 and keeping the other starting
The amount of protein in the diet modulates both total food intake and body weight gain. Many investigators have studied the relationship between dietary protein and food intake and weight gain, but
Are there any influential observations in the data analyzed in Problem 14.6B?
In an example in this chapter, we presented data relating to the effect of carotid sinus baroreceptors on nerve discharge. These data related very specifically to the function of a single
Do a complete analysis of the residuals and other regression diagnostics for the analysis of Problem 14.4B.
When patients are given certain antibiotics, they sometimes get an inflammation of the colon that is usually caused by a bacterium, Clostridium difficile, which produces an endotoxin. The mechanism
For the data analyzed in Problem 14.2, two observations had Studentized residuals ri greater than 2: r4 = 3.6, r7 = 2.43, h44 = .00159, and h77 = .193. Calculate the corresponding Cook’s distances.
Surfactant is a substance secreted by lung cells lining the alveoli, the small sacs at the end of airways in which gas exchange between air and blood occurs. Surfactant reduces surface tension and is
In Problem 4.4, you fit a curvilinear relationship between the change in rate of growth G in growth hormone H–treated children and their native H levels at the time treatment started. Fit these
Were the effects of low IADL different depending on the presence of comorbid conditions?
Keller and Potter also were also interested in whether the presence of other illness (comorbidities) such as heart disease, cancer, or AIDS affected mortality. Did considering the presence of
Taking care of elderly people on an outpatient basis is less costly than caring for them in nursing homes or hospitals, but health professionals have expressed concern about how well it is possible
Carrico and colleagues* also wanted to know whether stimulant drug use by HIV-positive gay men and also by their HIV-positive romantic partners was associated with HIV medication adherence in each
Kalkhoran and colleagues* investigated predictors of dual use of cigarettes and smokeless tobacco products. Although their original sample size was large (N = 1324), they were interested in running
A. Using the results of Problem 12.5, calculate the odds that a 65-yearold patient with low arterial oxygen, 6 kPa, and high protein index, 5.5, has ARDS. B. Make the same calculation for a
Is there any evidence that multicollinearity is a problem in the analysis done in Problem 12.5? Explain your answer.
Do a complete residual analysis on the logistic equation estimated in Problem 12.5.
Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. The usual diagnosis of ARDS is based on clinical findings of refractory respiratory failure and x-rays of
Is there a problem with multicollinearity in the data analyzed in Problem 12.3?
Sudden infant death syndrome (SIDS) is the condition in which infants die during their sleep without warning. Some people believe that SIDS frequencies at which important periodic fluctuations in
In the example of using stepwise (forward) regression to find the predictors of a positive exercise thallium test (nuking the heart), why does the degree of stenosis D enter the equation first (refer
A. Using the equation estimated for the example of Martian graduation, what are the odds that a Martian of 4 zorp will graduate? B. Of 12 zorp? C. From the answers to parts A and B, calculate the
A. Evaluate the residuals from the analysis of covariance you performed in Problem 11.9. Do they meet the assumption of a linear relationship between the response, F, and the covariate, L? If not,
There are many forms of heart disease, most of which eventually lead to heart failure, a condition in which the heart does not pump strongly enough to serve the needs of the body. Presumably, the
A. Test the assumption of homogeneity of slopes for the data you analyzed in Problem 11.7. B. Are you justified in proceeding with the comparison of adjusted means? If not, how do you interpret your
Calcium is an essential factor in the function of many cells, including the contraction of muscle cells. When blood pressure is elevated, as in hypertension, it is known that the intracellular
A. Test the assumption of homogeneity of slopes for the data you analyzed in Problem 11.5. B. Are you justified in proceeding with the comparison of adjusted means? If not, how do you interpret your
As transgenic mice have become more commonly used as models for research in cardiovascular disease, a question arose as to whether the normal mouse heart responded to ischemia (lack of blood flow)
For the “Ridding Your Body of Drugs” example (using the data in Table C-29, Appendix C), test the assumption of homogeneity of slopes.
For the secondhand smoke on Mercury example you analyzed in Problem 11.2 (using the data in Table C-28, Appendix C), test the assumption of homogeneity of slopes using an incremental F test.
Perform the analysis of covariance for the secondhand smoke on Mercury example (using the data in Table C-28, Appendix C).
For the “Fat-Free Exercising” example (using the data in Table C-27, Appendix C), test the assumption of homogeneity of slopes.
Perform a standard regression analysis in Problem 10.9 without including dummy variables to account for the between-dogs variability and then rerun the analysis including dummy variables to account
To study the physiology of the stomach and intestines, it is often necessary to measure the blood flow in a localized area in the wall of these organs. One standard method is to measure the
Suppose some of the data analyzed in Problem 10.7 were missing as shown in Table D-34, Appendix D. A. Analyze these missing data using the same analysis as in Problem 10.7. B. Are any of the
Strenuous exercise to which one is not accustomed can lead to muscle damage that is perceived as soreness in the afflicted muscles. Some evidence suggests that repeating a bout of exercise as much as
Suppose that some subjects gave incomplete responses to the sociability assessment analyzed in Problem 10.5A (the data are in Table D-32, Appendix D). A. Reanalyze the effect of antisocial
In this chapter, we analyzed three different personality scores—aggression, anger, and depression—in two groups of alcoholic subjects, those with antisocial personality disorder and those
Physical training causes adaptations in the metabolism of muscles, one of which is a switch in the energy sources utilized. To study the switch in energy metabolism as a result of exercise, Hood and
Bacterial contamination of surgical patients can occur from bacteria that contaminate the scrub suits worn by surgical personnel. During surgery, these scrub suits are covered by surgical gowns.
In this chapter, and in Problem 10.1, we analyzed the metabolic responses early (data in Table 10-1) and late (data in Table D-27, Appendix D) after a meal that dogs ate normally, but had their
In this chapter, we analyzed the metabolic rate response early after different methods of eating in dogs. The investigators also analyzed the metabolic rate later after the different types of eating.
When feeding cattle and sheep, sometimes a relatively poor quality feed, such as grass hay, must be used. Often this forage is supplemented with high levels of corn in the diet. Supplementing such
Repeat the analysis of Problem 9.9, leaving out the three-way interaction term. A. What effect does this omission have on the statistics and statistical conclusions? B. What effect does this omission
Many chemicals known as polycyclic aromatic hydrocarbons cause cancer. One of the best known of these is benzo(a)pyrine, which has many sources, including secondhand tobacco smoke. A related chemical
One approach to handling data in which there are empty cells in twoway and higher-order analyses of variance is to fall back on a one-way analysis of the remaining cells. Do a one-way analysis of
Evaluate the assumption of homogeneity of variance in the data of Problem 9.6 (Table D-24, Appendix D).
Nurse practitioner is a title granted to individuals with widely different training: from a short, continuing-education program to a 2-year program leading to a master’s degree. There is agreement
Suppose no data were obtained for cGMP levels in the pituitary gland when M was given, so there is a missing cell. A. Modify the data in Table D-22, Appendix D, accordingly and repeat the analysis of
Suppose that you were missing three data points from the study analyzed in Problem 9.3, one observation from the AOAA group and two observations from the M group in samples taken from the pituitary.
γ-Aminobutyric acid (GABA) is a nerve transmitter in the brain that has many functions that are not clearly understood. One such activity is control of secretion of the sex hormone prolactin from
Evaluate the assumption of homogeneity of variance for Problem 9.1.
Dietary fat is known to promote certain types of cancer. One of the ways certain fats may facilitate cancer is through a class of reactive chemicals derived from the fat, for example, arachidonic
Use the Holm–Sidak t test to do all possible comparisons of the data analyzed in Problem 8.6. Interpret the results in terms of the physiological question asked in Problem 8.6
Compute all possible comparisons among group means computed in Problem 8.6 using Bonferroni t tests. Interpret your results.
Evaluate the assumption of homogeneity of variances in the data analyzed in Problem 8.6 (the data are in Table D-20, Appendix D). If necessary, reanalyze the data and discuss any effect on the
Saliva contains many enzymes and proteins that serve a variety of biological functions, including initiating digestion and controlling the mouth’s environment. The latter may be important in the
Evaluate the assumption of homogeneity of variances in the data analyzed in Problem 8.4 (the data are in Table D-19, Appendix D). If necessary, reanalyze the data and discuss any differences from the
Sports medicine workers often want to determine the body composition(density and percentage of fat) of athletes. The typical way this is done is to weigh the individual in a tub of water to determine
Evaluate the normality assumption of the data used in the analysis of problem 8.1. If the data are not normally distributed, what can you do?
Evaluate the equality of variance assumption for the analysis of Problem 8.1 (the data are in Table D-18, Appendix D). If there is a problem, try to stabilize the variances. If successful in
Yoshida and coworkers* noted that a patient with myotonic dystrophy (a neuromuscular disease) had elevated blood calcium levels. A search of the clinical literature revealed other case reports that
Perform multiple imputation to address the missing data in the Martian data set described in the section “Missing Data Mechanisms Revisited:Three Mechanisms for Missing Martians” and perform the
Describe the remedies you would employ to address possible regression model assumption violations when fitting regression models using maximum likelihood estimation and multiple imputation.
Generate multiple imputations for the incomplete smoking, social networks, and personality data collected using the three-form design described in Table 7-6. Fit the regression model shown in Eq.
Take one of the data sets with multiple independent variables that appears in Chapters 3 or 4 and randomly delete 25–50 percent of values for one of the independent variables. Perform a multiple
Use a statistical program to compute the MLEs of the means, variances, and covariances for the complete copper-zinc data described in Chapter 4. Use the formulas shown in Eqs. (7.2) and (7.3) to
Take the original complete Martian data set and compute the log likelihood for one of the cases based on the multivariate normal log likelihood formula shown in Eq. (7.5). Use the maximum likelihood
Explain under what situation or situations that it matters little which missing data handling technique is used. (Hint: Under what circumstances do older, ad hoc methods for handling missing data
Explain why mean substitution is generally a poor method of handling missing data.
Name and define the primary method most statistical software programs use to handle missing data in their regression routines. List the limitations of that approach.
Schafer and Graham* discuss a hypothetical study in which blood pressure is measured at two time points. Assume that all subjects’ blood pressures were measured at the first time point. Now assume
Evaluate the predictive optimism of the final model you obtained in Problem 6.4 using h-fold cross-validation, leave-one-out crossvalidation, bootstrapping, or a similar technique. List the
Data analysts are often confronted with a set of few measured independent variables and are to choose the “best” predictive equation.Not infrequently, such an analysis consists of taking the
Reanalyze the data from the study of urinary calcium during parenteral nutrition (Problems 2.6, 3.8, and 5.5; data in Table D-5, Appendix D)using variable selection methods. Of the four potential
In Problem 3.17, we concluded that involuntary smoking was associated with an increased risk of female breast cancer, allowing for the effects of dietary animal fat. Are both variables necessary? The
For the regression analysis of Problem 3.12, what is the incremental sum of squares associated with adding T2 to the regression equation already containing T1?
Calculate from the last step shown in the computer output in Fig. 6-7.
Draw graphs illustrating the effect of centering on the relationship between C and C2 for the data in Table D-1, Appendix D.
Evaluate the extent of multicollinearity when using a quadratic equation to fit the data of Table D-1, Appendix D, relating sedation S to blood cortisol level C during Valium administration.
Use principal components regression to obtain parameter estimates for the regression model analyzed in Problem 5.7. A. What is the condition index of the correlation matrix? B. How many principal
Compare and interpret the eigenvalues and condition indices of the correlation matrix of the native and centered independent variables in the regression model analyzed in Problem 5.7.
Here are the eigenvalues of a correlation matrix of a set of independent variables: λ1 = 4.231, λ2 = 1.279, λ3 = .395, λ4 = .084, λ5 = .009, and λ6 =.002. A. How many independent variables are
In Problem 3.11, you used regression and dummy variables to see if two different antibiotic dosing schedules affected the relationship between efficacy and the effective levels of drug in the blood.
In Problem 4.3, you analyzed the relationship between ammonium ion A and urinary anion gap Uag. There was a suggestion of a quadratic relationship. A. Evaluate the extent of the structural
In Problem 3.8, you used multiple linear regression analysis to conclude that urinary calcium UCa was significantly related to dietary calcium DCa and urinary sodium UNa, but not to dietary protein
In Chapter 3, we fit the data on heat exchange in gray seals in Fig. 2-12(and Table C-2, Appendix C) using the quadratic function This equation describes the data better than a simple linear
For the multiple regression analysis of Problem 3.12, is there any evidence that multicollinearity is a problem?
In Table D-6, Appendix D, T1 and T2 are the two independent variables for the multiple regression analysis of Problem 3.12. Using only correlation analysis (no multiple regressions allowed),
A. Is multicollinearity a problem in the study of breast cancer and involuntary smoking and diet in Problem 3.17, excluding the interaction? B. Including the interaction? The data are in Table D-2,
. How are they similar or different?
Fit the quadratic model from Problem 4.14 using either the bootstrap method or computing robust standard errors. Evaluate the results and compare them with the quadratic model results obtained in
Evaluate the appropriateness of the linear model used in Problem 2.2. If indicated, propose and evaluate an alternative model. The data are in Table D-1, Appendix D.
A. Compare the regression diagnostics (Studentized residual, leverage, and Cook’s distance) computed in Problem 4.12 above with those obtained using a quadratic fit to the same data (see Problem
Evaluate the goodness of the fit of the linear model used to relate antibiotic effectiveness to blood level of the antibiotic in Problem 2.4(data in Table D-3, Appendix D). If the linear model is not
Repeat the regression analysis of Problem 2.4 (data in Table D-3, Appendix D) and compute Studentized residuals, leverage values, and Cook’s distances for the residuals and analyze the relative
Because the relationship between Breathalyzer-determined and selfreported blood alcohol levels in Problem 4.8 appeared to change above a certain level, we reanalyzed the data after throwing out the
In Problem 4.8, the data seem to reflect a threshold of about .10 blood alcohol in which a relatively good correspondence between Breathalyzer-determined blood alcohol and self-reporting of
Prepare a normal probability plot of the residuals from Problem 4.8.

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