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I use the model and estimated parameters to measure how workers value the better non-wage characteristics and on-the-job wage growth potential that result when unemployment insurance enables them to search longer. Accounting for these previously unmeasured benefits roughly triples my estimate of the program's value to workers. These results suggest an important role for non-wage characteristics in other applications throughout labor economics.

Methods: Three indices of work attributes (Status and Recognition, Physical Demands, and Exposure to Conflict) were derived by factor analysis of variables extracted from the Department of Labor's O*Net database. The indices were linked to the National Longitudinal Survey of Youth using occupation codes for the primary jobs held by women who gave birth between 1979 and 2000 and worked during the quarter prior to birth (n = 3,386 births to n = 2,508 mothers). Multiple regression was used to model birth outcomes as functions of the work attribute indices, controlling for several measures of socioeconomic status and risk factors for adverse birth outcomes.

Results: In the full sample, work-related Physical Demands were associated with lower average birthweight and increased odds of preterm birth while Status and Recognition was associated with higher average birthweight and lower odds of fetal growth restriction. In stratified models, Status and Recognition was associated with higher birth weight among women with low (versus high) income and with lower odds of preterm birth among women with low (versus high) education. Physical Demands were associated with higher rates of preterm birth among women with low (versus high) income and education and among African-American mothers (compared to Whites).

Conclusions: The work environment is an important predictor of healthy births. Relations between maternal work attributes and birth outcomes differ by race/ethnicity and socioeconomic status and according to the outcome under investigation. Further research with measures of work attributes specific to maternal work experiences is recommended to confirm our findings.

My dissertation research findings confirm that stratification research stands on a shaky foundation in ignoring family complexity. I show that models of intergenerational mobility which include family-level measures of class or educational background do a much better job of representing the mobility patterns in the data than conventional models do. Moreover, the choice of family background measure affects research conclusions. For example, I show that the apparent leveling of a long term trend toward greater equality in social class outcomes among recent male birth cohorts is actually due to the increasing but unmeasured effect of mothers' class resources on sons' outcomes. Rather than leveling off, inequality has increased noticeably compared to older cohorts. I also show that the lower predicted educational attainment of children raised in single parent families results from a comparatively weak relationship between absent parents' educational resources and children's educational success. This weak relationship exists only when parent-child involvement is low---when children spend sufficient time with absent parents, their achievement levels are close to those of young people who live full time with both parents.

The first chapter focuses on the skill accumulation of workers who have completed their formal education. Skills are acquired through work experience in the learning-by-doing (LBD) model. This model predicts that once hours of work are accounted for, there should be no systematic variation in wage growth. I use this prediction to test the LBD model by estimating, conditional on hours worked, the correlation between wage growth and variables affecting the incentives to accumulate skills. This correlation is found statistically significant and suggests a rejection of the LBD model for a sample of male and female workers from the National Longitudinal Survey of Youth (NLSY) 1979.

The second chapter is co-authored with Lance Lochner. We use the NLSY 1979 and NLSY 1997 to estimate the effects of family income on educational attainment in the early 1980s and early 2000s. The effects of family income on college attendance increase substantially over this period. We develop an educational choice model that incorporates both borrowing constraints and a "consumption value" of schooling. The model cannot explain the rising effects of family income on college attendance in response to rising costs and returns to college without appealing to borrowing constraints.

The third chapter is co-authored with Marc Frenette and Lance Lochner. We conduct a parallel empirical analysis of the effects of parental income on post-secondary (PS) education attendance for recent high school cohorts in both the U.S. and Canada using data from the NLSY 1997 and Youth in Transition Survey. We estimate smaller post-secondary education attendance gaps by parental income in Canada relative to the U.S., even after controlling for family background and adolescent cognitive achievement. We develop an intergenerational schooling choice model that sheds light on the role of potentially import ant determinants of the family income - post-secondary education attendance gap. We document Canada - U.S. differences in financial returns to PS schooling, tuition policy, and financial aid, discussing the extent to which these differences contribute to the stronger family income - attendance relationship in the U.S.

To interpret our empirical findings on college attendance, we develop an educational choice model that incorporates both borrowing constraints and a 'consumption' value of schooling - two of the most commonly invoked explanations for a positive family income - schooling relationship. Without borrowing constraints, the model cannot explain the rising effects of family income on college attendance in response to the sharply rising costs and returns to college experienced from the early 1980s to early 2000s: the incentives created by a 'consumption' value of schooling imply that income should have become less important over time (or even negatively related to attendance). Instead, the data are more broadly consistent with the hypothesis that more youth are borrowing constrained today than were in the early 1980s.

The abstract of this paper is as follows:
This dissertation examines labor markets in Silicon Valley in order to contribute to our understanding of the transformation of work and employment in the information economy. The relative newness of the region's economic structure, the dominance of information technology industries in the regional economy, and its role as the global center of innovation and production in these industries, make especially visible patterns of work and employment associated with the rise of information technology. Silicon Valley labor markets are characterized by high levels of flexibility, which is best understood by making a distinction between flexible work and flexibleemployment. The activities that workers perform on the job, the skills required, and the relationships they enter into to perform those activities are changing rapidly in unpredictable ways. Contractual relationships between employer and employee are increasingly characterized by high levels of turnover, short periods of employment, and employment contracts mediated by a set of institutions external to the firm. These dynamics are integrally linked with the character of competition in industries with a high dependence on information and knowledge, in which rapid innovation is critical for competitive success. Firms also pursue flexible employment, however, in an effort to cut costs and shift economic risk. In this environment, employers and workers are turning to a variety of third party intermediaries to help them navigate through an increasingly complex and shifting labor market. Three types of intermediaries are identified and described: 1) private-s ector, including temporary agencies, contractor brokers, professional employer organizations and web-based job search sites; 2) membership-based, including professional associations and union-based initiatives; and 3) public-sector, including employment placement programs and education-based initiatives. These intermediaries have contradictory influences on the labor market, in some cases undermining career opportunities for workers, and in other cases building improved career outcomes. Regardless of their impact, intermediaries have now become integral components of the region's labor markets, shaping the structure and dynamics of work and employment in fundamental ways. The prevalence of intermediaries in Silicon Valley suggests that they will become increasingly central to the structure and dynamics of contemporary labor markets in many regions.

Six subgroups of workers from a random sample of youth who entered the labor market in 1979 were studied: white women, black women, Hispanic women, white men, black men, and Hispanic men. Using an intersectionality framework, I establish that occupational injuries differ by race-gender. Race-gender differences in the initial odds of injury, time trajectories, and relationships between substantive predictors support an intersectionality framework. Differences in injury risk across time were documented and modeled using a Hierarchical Generalized Linear Modeling framework. Non-Hispanic white men began the study with the greatest risk of injury, while minority men had the lowest risk of injury. Across the 1990's differences between race-gender subgroups diminished. Non-Hispanic whites and black women have the greatest risk of injury in later waves.

Yet, little research has addressed the ways in which family structures and economic resources have impacted whether children grow up in households that do not include at least one biological parent. In order to address this gap, this paper offers a theoretical framework for estimating the effects of income and poverty, family structure, and income support policies on children's living arrangements. Its empirical implications are tested using data from the NLSY. The sample consists of 28,143 observations of families with children 18 years old or younger between 1986 and 1998. Probit models are used to estimate the probability that children from both single- and two-parent families are living in various out-of-home care arrangements. Results suggest that lower-income families, as well as single-parent and mother-partner families, are more likely to have a child living out-of-home in a given year. Higher AFDC/TANF benefits are associated with decreases in the probability that a family has a child living in a child welfare service setting, but increases in the probability that a family has a child living with relatives. Additionally, higher foster care payments are associated with increases in children living out-of-home.

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Berger, Hill and Waldfogel (2002) find that family leave coverage is associated with more breast-feeding and that children whose mothers did not have family leave coverage scored lower on tests of their cognitive ability at ages 3 and 4. They also document that women who return to work between 0 and 6 weeks following the birth of a child are less likely to breast-feed, to have taken their child to a well baby visit and to have had their child immunized.

METHODS: We used population-based longitudinal data from the National Longitudinal Study of Youth 1979 Cohort and Children of the National Longitudinal Study of Youth 1979 Cohort. Our analytic sample consisted of 29,318 child-year observations of 9011 children and their mothers observed annually or biennially from 1986 to 2008. We used the Behavioral Problems Index to measure socioemotional well-being. We used ordinary least squares regressions to estimate between-child associations of amounts and types of parental debt with socioemotional well-being, net of a host of control variables, and regressions with child-specific fixed effects to estimate within-child associations of changes in parental debt with changes in socioemotional well-being, net of all time-constant observed and unobserved confounders.

RESULTS: Greater total debt was associated with poorer child socioemotional well-being. However, this association varied by type of debt. Specifically, higher levels of home mortgage and education debt were associated with greater socioemotional well-being for children, whereas higher levels of and increases in unsecured debt were associated with lower levels of and declines in child socioemotional well-being.

CONCLUSIONS: Debt that allows for investment in homes (and perhaps access to better neighborhoods and schools) and parental education is associated with greater socioemotional well-being for children, whereas unsecured debt is negatively associated with socioemotional development, which may reflect limited financial resources to invest in children and/or parental financial stress. This suggests that debt is not universally harmful for children's well-being, particularly if used to invest in a home or education.

In this paper I focus on the labor supply and child care decisions of women immediately following birth, in order to evaluate the effects of mothers' decisions on the well-being of their children. In particular, I am interested in assessing the impact of both employment and child care decisions on children's cognitive ability. Previous studies have provided evidence that test scores measured early in a person's life have significant effects on future educational and labor market outcomes29. It seems at least interesting to try to understand whether there are any parental inputs that can enhance cognitive ability of individuals during their early stages of life. For this purpose I use data from the National Longitudinal Survey of Youth and, in particular, I look at the quarterly employment and child care histories of women after birth and until their child enters primary school at age 5. I assess the impact of these histories on Peabody Picture Vocabulary Tests scores and Peabody Individual Achievement Test scores (Math and Reading Sections). The key issue dealt with in the paper is the potential endogeneity problem that arises as a result of the existence of unobserved characteristics of both mothers and children. In fact, women are heterogeneous in both the constraints they face and their tastes. At the same time, children are heterogeneous in their cognitive endowments. As we would expect, mothers' decisions with respect to working when children are young, and/or placing children in child care are influenced by these heterogeneous characteristics of both mothers and children. Hence, children of working women or children of women that use child care will differ systematically from those whose mothers stay at home or do not use child care. This sample selection issue makes evaluation of the effects of women's decisions on child outcomes very difficult.

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The results indicate that the effect of child care use is negative, significant, and rather sizeable. In particular, an additional year of child care use is associated with a reduction of 2.8 percent (.15 standard deviations) in child test scores. But this general finding masks important differences across types of child care, children's ages, and maternal education. Indeed, only informal care used after the first year leads to significant reductions in child achievement. Formal care (i.e., center-based care and preschool) does not have any adverse effect on cognitive outcomes. In fact, these estimates imply that formal care has large positive effects on cognitive outcomes for children of poorly educated single mothers. Finally, the authors also provide evidence of a strong link between children's test scores at ages 4, 5, and 6 and their completed education.

We evaluate the effect of childcare vs. maternal time inputs on child cognitive development using the single mothers from the National Longitudinal Survey of Youth (NLSY79). To deal with non-random selection of children into childcare, we exploit the (plausibly) exogenous variation in welfare policy rules facing single mothers. In particular, the 1996 Welfare Reform, and earlier State level policy changes, generated substantial increases in their work/childcare use. Thus, we construct a comprehensive set of welfare policy variables, and use them (along with local demand conditions) as instruments to estimate child cognitive ability production functions. Because welfare rules are complex, we need many variables to characterize them. Thus, we face a "many instrument problem" (i.e., 2SLS severely biased toward OLS). We deal with this problem both by using LIML, and by using factor analysis to condense the instrument set. Results from the two approaches are very similar, and quite different from OLS. Using LIML along with factor analysis of the instruments leads to an efficiency gain (i.e., smaller standard errors) relative to using LIML alone. In our baseline specification, we estimate that a year of childcare reduces child test scores by 2.1% (.114 standard deviations). This estimate is quite robust across a wide range of specifications and instrument sets. But we find important interactions with type of care, maternal education and child gender. Indeed, only informal care leads to significant reductions in cognitive outcomes. Formal center-based care does not have any adverse effect. In addition, the value of the maternal time input is greater for more educated mothers, and girls are more adversely affect by childcare than boys. We do not find differential effects by child age or race/ethnicity.

Background: Childhood family structure is a commonly studied determinant of child and adult outcomes, but little is known about its effects on wealth accumulation. Wealth is affected by a wide variety of factors, including human capital formation, family dynamics, and intergenerational transfers. Studying wealth therewith sheds light on how childhood family structure relates to the accumulation of advantages across life.

Method: Data from the 1979 National Longitudinal Survey of Youth (N = 7,066) are employed to document wealth differences at ages 47 to 55. Growth curve models are estimated to understand at what ages these differences emerge.

Results: A median wealth penalty of at least $61,600 at ages 47 to 55 is observed for individuals who did not live continuously with both parents from birth to age 18, depending on the alternative childhood family trajectory considered. A subsequent mediation analysis of the "wealth penalty" related to the permanent departure of a parent from the household during childhood points at human capital formation and own family dynamics as the primary channels through which wealth differences are produced; intergenerational transfers matter rather less.

In each chapter we used two U.S. nationally representative data-sets (the Health and Retirement Survey RAND data-set, and the National Longitudinal Survey of Youth) to statistically estimate the probabilities of survival and transitions between states at each age with regression analysis. These probabilities were incorporated into discrete age and discrete state matrices. We examine age-specific state structure, the average remaining life expectancy, its variance, cohort simulations, dynamic heterogeneity and individual trajectories.

Method:The National Longitudinal Survey of Youth (1979; NLSY79) and NLSY-Child and Young Adult (NLSY_CYA) data are merged to create an intergenerational data set to compare generational disparities in immigrant offending across peers and within families. Differences in self-reported offending (prevalence and variety) by immigrant generation are assessed using a combination of descriptive analyses (χ2 and analysis of variance) and regression models.

Results: While NLSY_CYA children generally are at a greater risk of offending compared with the NLSY79 mothers, the difference in offending is greatest between first-generation mom and second-generation child dyads. Disparities in offending are driven in large part by exceedingly low levels of offending among first-generation immigrants.

Methods: A latent class growth analysis of health-related productivity loss was estimated on 12 waves of data from the National Longitudinal Survey of Youth (NLSY79) (N= 5699), an ongoing nationally representative longitudinal survey of Americans. Waves 1-5 were collected annually at ages 25-29 years. Waves 6-12 were collected biennially at ages 30-44 years. Productivity loss was measured as "health fully preventing a person from working" or "health limiting the amount or kind of work a person could do." Differences among trajectories were assessed using analyses of variance (ANOVA) and Chi-square tests.

Results: A five-group trajectory model for productivity loss was identified: (i) no risk, (ii) low risk, (iii) high risk, (iv) increasing risk at early ages, and (v) increasing risk at later ages. At the first wave, after the waves used for the trajectory model in which respondents were approximately age 45 years, the no-and low-risk groups worked the most weeks and hours per week and had the highest percentages of participants employed ≥10 weeks compared to the high-risk and early-/late-onset increasing-risk groups, all of which had the lowest levels of mastery, self-esteem, education, and socioeconomic status.

Conclusions: There are several developmental patterns of productivity loss, with some trajectories being associated with lower work participation in midlife. These high risk patterns may be indicative of individuals needing intervention to prevent premature work withdrawal.

We created a subsample of young women whose childbearing and marital histories we could follow: 2,783 women who were still participating in the survey in 1993 and who, at the time of the first interview in 1979, were under 20, had never been married, and had never given birth. Starting with 1979, we followed each of these women through subsequent surveys until they were 28 years old, between 1988 and 1993.

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Study 1 utilized a large cross-sectional national survey of working adults in the United States and found that college graduates who first looked for work during difficult economic times were more satisfied with their jobs well into their careers.

Study 2 found that people who graduated from both college and graduate school during times of higher unemployment were happier with their jobs both early in their careers and years later, even when they earned less money.

Study 3 replicated this effect in a different country, the United Kingdom, and among a more diverse educational population. Study 3 found that economic conditions at workforce entry predicted life satisfaction as well.

Finally, Study 4 explored potential mediators of this effect and suggested that people who entered the workforce during economic downturns were less likely to entertain upward counterfactual thoughts about how they might have done better. This tendency fully mediated the relationship between workforce economic conditions and job satisfaction. While past research on job satisfaction has focused on dispositional and situational antecedents, these findings suggest that strong experiential factors also may have an enduring effect on how satisfied people are with their jobs.

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Firstly, in one study cited in the article higher scores on the Rotter scale correlated with higher depression scores. However, the scale measures locus of control; it is not a measure of depression and thus is not a valid indicator of prior psychological state or prior depression.

Secondly, women included in the sample were categorised in the analysis according to marital status in 1992, yet data regarding first abortion or first unintended delivery are taken from 1980-92, with abortions and deliveries on average occurring between 1984 and 1986. Marital status in 1992 was not necessarily the marital status of women included in the sample during their first abortion or first unintended delivery. Thus basing the analysis and conclusions on the categories of married versus unmarried women is invalid and is not meaningful.

Given these observations, more rigorous analysis of the data is needed before any conclusions can be drawn about the link between depression and unintended pregnancy and marital status.

The first chapter presents a model in which young men find employment to enhance their value as marriage partners. When the effect of employment on marital value declines, young men's employment declines as well, in preparation for a less favorable marriage market. Taking this prediction to U.S. data, I estimate that fewer young men sought employment after 2 interventions that reduced the value of gender-role-specialization within marriage: i) the adoption of unilateral divorce legislation, and ii) demand-driven improvements in women's employment opportunities. I then use a structural estimation of the model to investigate interaction between the marriage market and male labor market shocks. Simulations find that the indirect effect of a negative shock to wages on young men's employment, operating through the marriage market, is nearly as large as the direct effect that operates purely through the labor market. These findings highlight the changing marriage market as an important driver of secular decline in young men's labor market involvement.

Our observations lead us to be skeptical of attempts to attribute the secular decline in male labor-force participation to a series of separately-acting causal factors. We argue that the correct interpretation probably involves complicated feedback between falling labor demand and other factors which have disproportionately affected men without a college education.

Concern about slackening productivity growth and deteriorating competitiveness has resulted, in many nations, in a new public focus on the quality and rigor of the elementary and secondary education received by the nation's front line workers. Higher order thinking and problem solving skills are believed to be in particularly short supply so much attention has been given to mathematics and science education because it is thought that these subjects are particularly relevant to their development.

Concern about slackening productivity growth and deteriorating competitiveness has resulted, in many nations, in a new public focus on the quality and rigor of the elementary and secondary education received by the nation's front line workers. Higher order thinking and problem solving skills are believed to be in particularly short supply so much attention has been given to mathematics and science education because it is thought that these subjects are particularly relevant to their development.

We use two data sets for the U.S. The first sample is taken from the National Longitudinal Survey of Youth (NLSY79) and the second is the 2000 wave of the NLSY-Child which contains information from 3,425 women with 8,323 children. Combining information from the NLSY79 marital/cohabitating history of their mothers and questions about family structure in the NLSY-Child we create a family structure history. This allow us to distinguish between children living with married biological parents, cohabiting parents, single mothers, mothers married to stepfathers, and mothers cohabiting with unrelated males. We use a number of educational outcomes. For children from ages 5 to 15 we have assessment instruments including three Peabody Individual Achievement Tests (PIAT) for reading and math and the Behavior Problems index which measures a child's anti-social behavior. For children over the ages of 15 we observe school enrollment status and highest grade completed. Explanatory variables include demographic characteristics, parental education, number of siblings, and family income.

For Sweden we use a random sample of children born 1974-84 drawn from the population registers. The data sample roughly 20 percent of Swedish children born each year from 1974-84 and their siblings. The total sample size is over 300,000 child observations. This data is combined with family and individual information from the censuses from 1965, 1970, 1975, 1980, 1985 and 1990. Our outcome variables are grade point average at age 16, high school graduation at age 19, and years of schooling and earnings for older children in the sample. We create marital history--length of cohabitation and length of marriage-- for the parents using information from the bidecennial censuses from 1990 and before and tax records after 1990. Our explanatory variables include the sibling composition of the household (his children, her children, and their joint biological children), the educational attainment and earnings of the adults in the household, and whether the family lives in an urban area.

Identifying the causal effect of marriage on outcomes is complicated by the selection problem. We use IV-methods as well as fixed-effect models to deal with this problem.

This calculus, when applied to large numbers of workers, allows a researcher to calculate the value of a statistical life, or the wage reduction associated with reducing the expected number of deaths by one worker. As this value represents the amount of wages that workers are willing to forgo to reduce risk, the value of a statistical life appears to be a useful tool for evaluating individuals' willingness to pay for reductions in risk in other areas. Indeed, it is a measure of the price of risk. The Environmental Protection Agency (EPA) often considers regulations that both impose costs on industry and reduce the deaths from environmental contamination. While the costs may often be calculated with a great deal of accuracy, the problem for policymakers is to value the corresponding benefits. The price of risk appears to be a useful tool for such evaluations.

When basing policy on estimates of the price of risk, the precision and accuracy of the estimates become of utmost importance. Yet, Viscusi (1993), in his review of labor market studies of the value of life, reports that the majority of the estimates are in the $3 to $7 million range [in December 1990 dollars, p. 1930], and this range excludes studies that Viscusi felt were flawed. While this represents over a 133 percent variation, Viscusi correctly notes that much of the variation should be expected, as the studies used different methodologies and different samples. Workers may differ in their attitudes toward risk, and the mixes of workers in these various studies differ substantially. His review, however, leaves unanswered how much of this variation results from differences in the sample of workers, measures of job risk, and the specification of the estimating equation.

In this report, we use three data sets to estimate the price of risk: the Outgoing Rotation Groups of the Current Population Survey, the March Annual Demographic Supplement of the Current Population Survey, and the National Longitudinal Survey of Youth (1979). Labor economists frequently use these three data sets to estimate wage equations. We match these data to two sources of job risk data: the Bureau of Labor Statistics estimates from their Survey of Working Conditions and the National Institute of Occupational Safety and Health estimates from their National Traumatic Occupational Fatality survey. We then use these data to estimate the price of risk.

EDITOR—Reardon and Cougle claim no conflict of interest in their paper. However, the principal author (Reardon) is a professional anti-abortionist and the funding organisation for which he works has as its primary aim propagandising against abortion. Therefore the sampling, the methods, the statistics, and the conclusions should be rigorously evaluated.

Introduction -- Career and family : college women look to the past -- Labor supply effects of state maternity leave legislation -- Working mothers then and now : a cross-cohort analysis of the effects of maternity leave on women's pay -- Parental leave policies in Europe and North America -- Work norms and professional labor markets -- Early career supervisor gender and the labor market outcomes of young workers -- Three perspectives on policy.

Papers presented at a conference held in April 1995 at the New York State School of Industrial and Labor Relations, Cornell University./ Includes bibliographical references (p. 285-295) and index.
2000 edition: 1st paperback ed.

Design/methodology/approach: Using a sample of 234 self-employed entrepreneurs from a longitudinal database, regression analysis was employed to examine the predictors of venture performance. A hazard model was utilized to assess venture survival.

Findings: Entrepreneurs' intelligence influenced venture performance directly and indirectly via educational attainment. Entrepreneurs with higher GMA were subsequently able to obtain more education, and GMA had an indirect, positive influence on venture performance through this additional educational attainment. Findings also demonstrated an inverted-U, curvilinear effect on venture survival for GMA and educational attainment. This indicates that both intelligence and educational attainment should be considered when examining how likely entrepreneurs are to persist or survive in their ventures.

This analysis focused on six key bets, or pathways for improving social mobility, which Bridgespan identified in consultation with experts at the Urban Institute. These six areas of focus were 1) improving early childhood development, (2) establishing viable pathways to careers, (3) reducing unintended pregnancies, (4) decreasing overcriminalization and overincarceration, (5) creating place-based strategies to improve access to opportunity across regions, and (6) building continuous learning and improvement capacity of social service providers. Using the Social Genome Model, the authors were able to size the potential impact of investments in these core areas.

Theories that have been utilized in examining the effects of inter-group marriages, especially inter-racial marriages, on the behavior of couples provide theoretical guidance for the analysis. Largely, this research, as well as research on other differences between husbands and wives, indicates that inter-group married couples have higher migration rates than intra-groups couples. Data from the National Longitudinal Survey of Youth in 1979 are used to analyze the relationships between these aspects of religious identities and migration and between church attendance and migration. Results actually show slightly lower migration odds for inter-group couples than for intra-group couples. Thus, our hypothesis is rejected.

This volume represents a comprehensive treatment of a model sometimes referred to as latent curve or growth curve models. Latent Curve Models analyzes LTMs from the perspective of structural equation modeling (SEM) with latent variables. Although the authors discuss simple regression-based procedures that are helpful in the early stages of LTM, most of the presentation will use SEMs as a driving tool throughout the text.

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