Multiple Regression And Beyond 2nd Edition Timothy Z. Keith - Solutions

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1.35 State which of the following is an example of sampling with replacement and which is an example of sampling without replacement.a. Selecting 10 patients out of 100 to test a new drugb. Selecting one professor to be a member of the university senate and then selecting one professor from the
1.34 Indicate whether each of the following examples refers to a population or to a sample.a. Salaries of CEOs of all companies in New York Cityb. Five hundred houses selected from a cityc. Gross sales for 2009 of four fast-food chainsd. Annual incomes of all 33 employees of a restaurant
1.33 Indicate whether each of the following examples refers to a population or to a sample.a. A group of 25 patients selected to test a new drugb. Total items produced on a machine for each year from 1995 to 2009c. Yearly expenditures on clothes for 50 personsd. Number of houses sold by each of the
1.32 Refer to Exercises 1.30 and 1.31. Classify these data sets as either cross-section or time-series data.
1.31 The following table gives the total 2009 payrolls (on the opening day of the 2009 season, rounded to the nearest million dollars) for eight National League baseball teams.Total Payroll Team (millions of dollars)Atlanta Braves 97 Chicago Cubs 135 Florida Marlins 37 Los Angeles Dodgers 100 New
1.30 The following table gives the total number of DVDs sold at retail stores between 2003 and 2008.U.S. Retail Sales of DVDs Year (millions of DVDs)2003 11.3 2004 15.1 2005 16.0 2006 16.3 2007 15.8 2008 15.2 Source: SNL Kagan.Describe the meanings of a variable, a measurement, and a data set with
1.29 The number of students (rounded to the nearest thousand) currently enrolled at seven universities is 7, 39, 21, 16, 3, 43, and 19, respectively. Let x be the number of students currently enrolled at a university.Find:a. xb. 1x22c. x2
1.28 Prices (in thousands of dollars) of five new cars are 28, 35, 39, 54, and 18, respectively. Let x be the price of a new car in this sample. Find:a.b. c.
1.27 The number of pizzas delivered to a college campus on six randomly selected nights is 48, 103, 95, 188, 286, and 136, respectively. Let x denote the number of pizzas delivered to this college campus on any given night. Find:a.b. c.
1.26 Eight randomly selected customers at a local grocery store spent the following amounts on groceries in a single visit: $216, $184, $35, $92, $144, $175, $11, and $57, respectively. Let y denote the amount spent on groceries in a single visit. Find:a.b. c.
1.25 The following table contains the same kind of information as the table in Exercise 1.24 but for the NCAA Women’s Basketball Championship tournament Final Four teams for 28 years from 1982 to 2009.Seed 1 2 3 4 5 6 7 8 9 Number of Teams in Women’s Final Four 59 27 12 8 1 2 1 1 1 Let y denote
1.24 The following table contains information on the NCAA Men’s Basketball Championship tournament Final Four teams for the 31-year period from 1979 to 2009. The table shows how many teams with each seeding qualified for the Final Four during these 31 years. For example, 53 of the 124 Final Four
1.23 The following table lists six pairs of m and f values.m 3 6 25 12 15 18 f 16 11 16 8 4 14 Calculate the value of each of the following:a.b. c. d.
1.22 The following table lists five pairs of m and f values.m 5 10 17 20 25 f 1 28 6 1 64 Compute the value of each of the following:a.b. c. d.
1.21 Classify the following as cross-section or time-series data.a. Average prices of houses in 100 citiesb. Salaries of 50 employeesc. Number of cars sold each year by General Motors from 1980 to 2009d. Number of employees employed by a company each year from 1985 to 2009
1.20 Classify the following as cross-section or time-series data.a. Food bill of a family for each month of 2009b. Number of armed robberies each year in Dallas from 1998 to 2009c. Number of supermarkets in 40 cities on December 31, 2009d. Gross sales of 200 ice cream parlors in July 2009
1.19 Briefly describe internal and external sources of data.
1.18 Explain the difference between cross-section and time-series data. Give an example of each of these two types of data.
1.17 Classify the quantitative variables in Exercise 1.15 as discrete or continuous.
1.16 Classify the quantitative variables in Exercise 1.14 as discrete or continuous.
1.15 Indicate which of the following variables are quantitative and which are qualitative.a. Number of typographical errors in newspapersb. Monthly TV cable billsc. Spring break locations favored by college studentsd. Number of cars owned by familiese. Lottery revenues of states
1.14 Indicate which of the following variables are quantitative and which are qualitative.a. Number of persons in a familyb. Colors of carsc. Marital status of peopled. Time to commute from home to worke. Number of errors in a person’s credit report
1.13 Explain the meaning of the following terms.a. Quantitative variableb. Qualitative variablec. Discrete variabled. Continuous variablee. Quantitative dataf. Qualitative data
1.12 Refer to the data set in Exercise 1.10.a. What is the variable for this data set?b. How many observations are in this data set?c. How many elements does this data set contain?
1.11 Refer to the data set in Exercise 1.9.a. What is the variable for this data set?b. How many observations are in this data set?c. How many elements does this data set contain?
1.10 The following table gives the state taxes (in dollars) on a pack of cigarettes for nine states as of April 1, 2009.State Tax State (in dollars)Alaska 2.00 Iowa 1.36 Massachusetts 2.51 Missouri .17 New Hampshire 1.33 New York 2.75 Ohio 1.25 South Carolina .07 West Virginia .55 Briefly explain
1.9 The following table gives the number of dog bites reported to the police last year in six cities.City Number of Bites Center City 47 Elm Grove 32 Franklin 51 Bay City 44 Oakdale 12 Sand Point 3 Briefly explain the meaning of a member, a variable, a measurement, and a data set with reference to
1.8 Explain the meaning of an element, a variable, an observation, and a data set.
1.7 Explain whether each of the following constitutes a population or a sample.a. Number of personal fouls committed by all NBA players during the 2008–2009 seasonb. Yield of potatoes per acre for 10 pieces of landc. Weekly salaries of all employees of a companyd. Cattle owned by 100 farmers in
1.6 Explain whether each of the following constitutes a population or a sample.a. Pounds of bass caught by all participants in a bass fishing derbyb. Credit card debts of 100 families selected from a cityc. Number of home runs hit by all Major League baseball players in the 2009 seasond. Number of
1.5 Briefly explain the difference between a census and a sample survey. Why is conducting a sample survey preferable to conducting a census?
1.4 Give one example each of sampling with and sampling without replacement.
1.3 Briefly explain the terms population, sample, representative sample, random sample, sampling with replacement, and sampling without replacement.
1.2 Briefly explain the types of statistics.
1.1 Briefly describe the two meanings of the word statistics.
Life will turn out better for you than it has for your parents?”
You will have good friends you can count on?
You will be respected in your community?
You will be able to live wherever you want in the country?
You will stay in good health most of the time?
You will have a happy family life?
You will have a job that you enjoy doing?
You will be able to own your own home?
You will have a job that pays well?
You will go to college?
You will graduate from high school?
Δdf, RMSEA, SRMR, CFA, and AIC, although your instructor may have different preferences.
e. Provide a table of fits of the various models. I suggest including χ2 and df, Δχ2 and
d. Add the variables Age, Parent Alcoholism, and Rebelliousness as possible explanatory variables in a conditional LGM. Does parent alcoholism affect adolescents’drinking behavior? Does adolescent rebelliousness affect drinking? What do those effects mean? Briefly interpret any statistically
c. Interpret your final unconditional model. What do the means and variances of the Drinking intercept and Drinking slope tell you? Are these two latent variables correlated? What does that correlation tell you?
b. You may need to constrain the error variances for Adol1 and Adol3 to zero (to avoid negative values). What happens to the fit of this model? (These constraints will not be needed for the conditional model with explanatory variables.)
a. Develop an unconditional LGM to explain the developmental trajectory among these youth in drinking behavior. Start with a model in which the error variances for Adol1 through Adol3 are constrained to be equal. Does the fit improve when you free this constraint in a second model?
2. Does being the child of an alcoholic influence adolescent drinking behavior? Curran, Stice, and Chassin examined the growth in adolescents’ alcohol, along with that of their peers, over a three-year period (Curran, Stice, & Chassin, 1997). Here we will use a portion of the data to examine the
1. Conduct the analyses outlined in this chapter. The data are in the file labeled “math growth final.sav.” See the website (www.tzkeith.com) for initial setup for these models for Amos and Mplus.
â•›â†œi) Would you be willing to accept configural invariance (step a)? Metric invariance?Intercept invariance? Briefly explain why or why not.
h) Provide a table of fit statistics for the models listed in steps a through g. Be sure to list the corrected RMSEA.
g) Test the equivalence of the latent means for self-concept using a model constraint and fit statistics. Do boys and girls differ in their levels of self-concept? Why do you come to that conclusion? Briefly interpret your findings from questions f and g (e.g., who, if anyone, scored higher?).
f) Test the equivalence of the latent means for locus of control using a model constraint and fit statistics. Do boys and girls differ in their levels of locus of control?Why do you come to that conclusion?
e) Based on the text output, does it appear that boys and girls differ in their overall latent mean level of self-concept? Locus of control? On what did you base this conclusion? If you concluded that there were differences, which sex scored higher, and by how many points?
d) Test intercept invariance (aka strong invariance; you do need to estimate means &intercepts at this step).
c) Test metric invariance across groups.
Table 19.9 Self-Concept and Locus of Control Items for Exercise 3. Each item’s response choices ranged from 1, strongly agree, to 4, strongly disagree. As shown, positively worded items were reversed so that for all items a high score represents a high self-concept or a high (internal) locus of
b) Add a covariance between the errors of measurement for items BYS44Dr and BYS44Er.bys44ar bys44dr bys44er bys44b bys44c bys44f bys44hr Self Concept Locus of Control Figure for text Conceptual model Figure 19.18 Conceptual model for Exercise 3: invariance of self-concept and locus of control for
a) Test this initial model across groups (configural invariance). You do not need to estimate means & intercepts at this step (but I recommend that you do so).
2.xls” with a separate tab for boys and girls (there is also a tab with the full matrix).Note that the four self-concept items have been reversed so that for all items a high score represents a positive self-concept or an internal locus of control. Note also that the figure shown below represents
3. Test the invariance of shorter self-concept and locus of control scales from NELS across sex. The proper composition of these scales is represented in Figure 19.18. A reminder of the item wording is shown in Table 19.9. The data are in the excel file “sc loc matrix
2. Conduct the higher-order invariance tests as outlined, but not detailed, in this chapter.Make sure your degrees of freedom match those shown in Table 19.8 below for each model:Table 19.8 Degrees of Freedom to the Higher-Order Invariance Tests, Exercise 2 Configural 140 Metric 151 Intercept 161
3. Figure 18.26 shows a dummy variable model designed to test the effect of Sex on the change in Locus of Control from 8th to 10th grade (or 10th-grade Locus controlling for 8th-grade Locus). Analyze the model using the NELS data. You should recode the Sex variable or create a new Sex dummy
Figure 18.25 Initial MG-MACS model to study levels of homework and grades and effects of homework on high school grades for boys versus girls.effect of Homework on Grades to vary across groups. Does homework have the same effect on grades for boys and girls, or does the effect of homework depend
2. Figure 18.25 shows a starting model for a MG-MACS analysis of the effect of Homework on 12th-grade GPA. The model for boys is shown. A starting model for Amos (with variable names but without cross-group constraints) is available on the website (www.tzkeith.com). Also on the website are the raw
f. Specify an alternative model in which Locus8 is allowed to affect Locus12 and Ach8 is allowed to affect Ach12. Are the effects statistically significant? Are they meaningful? How did you decide?
e. Specify an alternative model to answer the question of whether SES has any direct effects on 10th-grade locus of control and achievement. Next test for direct effects on 12th-grade Locus and Achievement. Are the effects statistically significant? Are they meaningful? How did you decide?
d. Specify two alternative models to determine, based on fit, whether Ach affects Locus, and whether Locus affects Ach. Why is Δχ2 not a good choice for these comparisons?What might you examine instead?
c. Using the concepts of setting parameters to be the same from the multi-group section of the chapter, constrain the factor loadings of the Locus factor to be the same over time. That is, constrain the loadings for luck8, luck10, and luck12 to be the same, constrain the loadings for stops8,
b. Examine the modification indexes and standardized residuals to determine if there are other model modifications you might make to improve fit. Do you have a theoretical justification for doing so? How can the modification indexes be so large in a model that generally fits well?
a. Given the nature of the measured variables, are there any correlated errors you might add a priori to improve model fit? Consider, in particular, if some of the Locus items measure something in common other than general locus of control.
3. Analyze the latent variable panel model of locus of control and achievement. The data are in the file “sc locus ach matrix n12k.xls,” and more information about the variables is shown in the related codebook file. Estimate the model as shown in the figure; make sure your results match those
c. Compare the fit of this model with one in which Mother’s Expressivity is also allowed to have direct effects on the two child outcomes. Based on the change in fit, would you say that children’s Regulation completely or partially mediates the effect of Mother’s Expressivity on Behavior
2. Nancy Eisenberg and colleagues (2001) conducted research to determine the effects of mothers’ emotions on their young children’s behavior problems and social competence. One interest in the research was whether these effects are mediated by children’s own emotional regulation. Figure
1. If you have a full-featured SEM program, analyze the series of full homework models starting with the model shown in Figure 17.1. Make sure your results match those presented here. If you are using a student version of a program that places a limit on the number of variables you can analyze,
Estimate the model shown. Create a table of direct, indirect, and total effects on the final outcome (Attained Occupation). Which variables are the most important influences on these men’s eventual occupations? Which variables are less important? Interpret your findings. Is there anything
3. Kimmo Sorjonen and colleagues used SEM to estimate the relative effects of intelligence, family of origin SES, and emotional capacity (at the time of their conscription into the military) on Swedish men’s occupational status at ages approximately 35-40(Sorjonen, Hemmingsson, Lundin,
a. Draw (set up) and estimate the model. Is the structural portion of the model justidentified or overidentified? Evaluate the fit of the model and, if adequate, focus on parameter estimates. Interpret the model. According to these results, does Head Start have a positive effect on cognitive
2. Figure 16.13 shows a model to test the effects of participation in Head Start on children’s cognitive ability. This example is a classic reanalysis of a controversial quasiexperiment; I have seen variations of it presented in Kenny (1979) and Bentler and Woodward (1978), among others. The
1. Analyze the simulated Buhs and Ladd data (“Buhs & Ladd data.sav” or Buhs & Ladd data.xls”) using a structural equation modeling program (if you are using Amos, the initial model is saved as “Buhs & Ladd 1.amw”; the Mplus script is also online).a. Estimate the models discussed in this
3. The files “DAS 5–8 simulated 6.sav” and “DAS 5–8 simulated 6.xls” include 500 cases of simulated data for the DAS-II.
2. The NELS data include a series of items (ByS44a to ByS44m) designed to assess students’ self-esteem and locus of control. Choose several or all of these items that you believe best measure self-esteem and locus of control and subject them to confirmatory factor analysis. First use SPSS (or
1. Conduct the analyses outlined in this chapter. If you have a student version program that only allows a certain number of variables, you may be able to estimate a portion of the models. The initial four-factor model is on the accompanying Web site (www.tzkeith.com) as the file “DAS-II first
2. How could you convert this research from a measured variable study into a latent variable study? Think of ways to include multiple measures of the researchers’ independent and dependent variables. Draw a model incorporating both measured and latent variables.
Analyze each data set without variable X2 in the model. What happens to the magnitude of the path from X3 to Y1?Figure 13.22 Understanding common versus non-common causes, and their effects on path estimates.Now conduct the same analyses with the data set in “common cause 3.sav.” Note the
Analyze these data using an SEM program. For both data sets, the model you should estimate is illustrated in Figure 13.13. Compute and examine the correlations among the variables in both data sets. All correlations are statistically significant, correct?Now analyze the model shown for both data
7. Exercise 6 in Chapter 4 was “designed to explore further the nature of common causes, and what happens when non-common causes are included in a multiple regression. We will begin our analysis of these data here, and will return to them in Part 2 when we have the tools to explore them more
6. Estimate the nonrecursive trust model from Figure 13.17. The model (trust nonrecursive model 1.amw) and the data (trust norec sim data.xls) are included on the accompanying Web site. Second, assume that the Man’s Trust affects his partner, but not the reverse: delete the path from Woman’s
Data consistent with those reported in the original article are in the SPSS file “Henry et al.sav” or the Excel file “Henry et al.xls.” Analyze and interpret this model. Which variable had a more important effect on boys’ delinquency: peers who are delinquent or peers who are violent?
5. Henry, Tolan, and Gorman-Smith (2001) investigated the effect of one’s peers on boys’later violence and delinquency. Figure 13.21 shows one model drawn from their study, their “fully mediated” model. Family Relationships is a composite of measures of family cohesion, beliefs about
4. Focus on the equivalent models in Figure 13.14. Note the difference between these and the initial model (model A). Which rule or rules were used to produce each equivalent model? Check your answers against those in note 5. Try estimating one or two of these models to demonstrate that they are
Calculate the direct, indirect, and total effects of these two variables on Social Studies Achievement. Whichever way you drew the path, now reverse the direction and re-estimate the model. Recalculate the direct, indirect, and total effects of these variables on Social Studies. Explain the
b. Did you draw a path from Self-Esteem to Locus of Control or Locus of Control to Self-Esteem?
3. In Chapter 11, you constructed and tested a path model using the variables Family Background (BYSES), 8th-grade GPA (BYGrads), 10th-grade Self-Esteem (F1Concpt2), 10th-grade Locus of Control (F1Locus2), and 10th-Grade Social Studies Achievement(F1TxHStd). Refer to or redo the analysis. For the
2. Find an article that uses path analysis or explanatory multiple regression on a research topic with which you are familiar and interested. If the authors’ model is not drawn in the article, see if you can draw it from their description. How do the authors justify their causal assumptions or

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Multiple Regression And Beyond 2nd Edition Timothy Z. Keith - Solutions

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