Dependent Variables. Economic Governance Institu- tions Hall and Soskice (2001) differentiated between two ideal types of governance sys- tems: liberal and coordinated. Because they were primarily concerned with broadly characterizing the ideal types and their innovational outcomes, they did not provide precise indicators. Xxxxx Xxxxxx (2005) has criticized this reliance on dichotomous ideal types because it does not allow for the capture of important gradations, unex- pected hybrids, or changes over time. Rather, he advocates evaluating the strength of each possible governance institution for every observation. By evaluating ‘degrees of coordination’ in corporate governance institutions, Gourevitch and Xxxxx (2005) offer clearer indicators and a more ordinal measure, along the lines recommended by Xxxxxx. But because they still base their analysis on a dichotomous typology, they mischaracterize observations that have stronger coordinating institutions than exist in liberal systems but that operate with a different internal logic than coordinated institutions. Though the VoC scholars have identified five such institutions, I am focusing on two: inter-firm linkage and corporate governance institutions. I also evaluate recent research by Xxxxxxx (2010) concerning a third, worker training institutions. Corporate governance institutions structure the relationship between investors and firms. They are central to much of the work on this literature (Gourevitch, 2003; Gourevitch & Xxxxx, 2005; Gourevitch & Xxxxx, 2002) and have a powerful impact on the structure of the economy as a whole. Inter-firm linkage institutions structure the relationships among firms, both horizontally and vertically. Linkages and linkage institutions such as business associations are often cited as important by the devel- opment literature (Brimble & Xxxxx, 2007).9 I expect that there will be a lag in the 9I anticipate that corporate governance institutions will be the most pliable, that inter-firm linkage institutions will take longer to develop, and that worker training institutions will take the longest to develop. This is not so much because corporate governance institutions ought to be especially easy to develop, but because the complementarities noted in the VoC literature may make some institutions more essential than others. Hall and Soskice argue that each of the economic governance institutions may strengthen and reinforce each of the others. While this seems to be true, it may be that some have a...
Dependent Variables. Variables measured in the Experiment 2 are listed below in the order as they were measured during the experiment. Demographic variables Participants reported their gender, age, education level, and employment status. The main research questions (RQ)
Dependent Variables. In the analyses that follow, the dependent variable is an indicator equal to one if the couples have divorced or separated (if married) or broken up (if cohabiting). In order to maintain a plausible causal order from money management (and changes in money management) to union disruption, this measure is taken from the 60-month survey.
Dependent Variables. 65 Survey Findings for Research Questions 1 and 2...................................................... 67 Findings for Research Question 3 ............................................................................. 71 School/Community Violence ........................................................................ 72 Physical Abuse .............................................................................................. 72 Bullying ......................................................................................................... 73 Complex Trauma ........................................................................................... 74 Sexual Abuse ................................................................................................. 74 Medical Trauma............................................................................................. 75 Summary.................................................................................................................... 76 CHAPTER 5: DISCUSSION ................................................................................................ 78 Summary of the Study ............................................................................................... 79
Dependent Variables. The research questions for this study included two dependent variables: teacher trauma (well-being) and teacher retention. The researcher ran a Xxxxxxx linear correlation between specific survey items to determine if there was an interrelationship between them, and they could be used for the two constructs, teacher trauma, and retention. Table 5.1 reports the Xxxxxxx correlation coefficients for the construct perceptions of teacher PTSD/Trauma, using survey items “experience painful images/thoughts/memories,” “avoid thoughts or feeling related to trauma,” “avoid places/people/conversations or activities that remind them of trauma,” “are irritable,” and “fearful or easily startled due to work-related trauma.”
Dependent Variables any ER utilization and ER expenditure The dependent variables in this study are 1) any ER utilization and 2) conditional predicted ER expenditure, a continuous variable for the total ER facility and doctor expenses. The statistical analysis which will we elaborate on in the next paragraph focused on any ER utilization in the first part of the model, a recoded binary variable yes (1) or no (0). The second part of the model uses total ER expenses.
Dependent Variables. Study 2, Individual Level, Classification Consistency For individuals, we addressed the classical statistical question whether a particular sample result is repeatable in a new sample. For measurement, repeatability refers to re-administering the same test to the same individuals a great number of times, and then determining to which degree the same conclusion about an individual was drawn. Figure 1 shows two propensity distributions (the small distributions) and the corresponding proportions p of correct classification—rejection for person A and selection for person B. Obviously, proportion p is larger as someone’s true score is located further away from the cut score, and the question is whether short tests produce too many small p values; that is, too many applicants on either side of the cut score that would be misclassified too often based on repeated observation of their test performance. Xxxxx and colleagues (2007) suggested that organizations set a lower bound to p, so that they make explicit what they think is the minimally acceptable certainty one requires for decisions about an individual. For example, an organization could require p to be at least .9, meaning that upon repetition an individual may be not be Downloaded by [Radboud Universiteit Nijmegen] at 06:01 04 November 2013 + − − + = = − + misclassified more often than in 10% of the test repetitions. Thus, for the propen- sity distribution on the right in Figure 1 the unshaded area must cover no more than 10% of the total area. The quality of a particular personnel-selection scenario and a particular test or test battery may be measured by the proportion of unsuited individuals (for whom T < XC) that have p values of .9 or higher; this is called classification consistency and denoted CC (the minus sign refers to the rejection area). Likewise, the classification consistency CC for the selection area could be determined. Large CC values suggest that the personnel-selection scenario and the test or test battery used produce certainty about individual decisions for many ap- plicants. The question is whether CC and CC are large enough when short tests are used. We studied CC and CC for lower bound values p .7 and p .9. + − Xxxxxxxxx and Xxxxxx (1997) and Xxxxxxx and Xxxxxx (2002) discussed similar approaches to rejection/selection problems but used different outcome measures; see Emons and colleagues (2007) for a critical discussion of their approaches. The latter authors concluded that the clas...
Dependent Variables. The QLTE survey is designed to measure the extent educators agree or disagree with specific elements of the five domains of working conditions. For each domain, a series of statements assess various components of the working condition and records the educator‘s level of agreement through their response on a Likert scale [range 1 = ―strongly disagree‖ to 5 = ―strongly agree‖]. Since the aim was to assess the impact of 8 Pseudonyms are used throughout the dissertation to protect the confidentiality of all respondents. NCLB sanctioning on working conditions, I created a single measure of each domain to be used as a dependent variable. Thus, I needed to find a meaningful combination of these statements to formulate a single measure that gauges the importance of that working condition domain for the respondent. To do this I utilized factor analysis techniques for data reduction purposes. I used principal-components factor analysis with orthogonal varimax rotation to reduce the data and determine the proper selection of items within each working condition domain. Most items within each domain loaded cleanly along a single factor. Using a cut off of factor loadings greater than .55, a generally accepted indicator for ―good‖ fit, I narrowed the items to a single set used to measure the domain. This procedure produced a single factor structure for each of the following working conditions: time (Chronbach‘s α=.7748), facilities and resources (Chronbach‘s α=.7836), empowerment (Chronbach‘s α=.9298), and professional development (Chronbach‘s α=.9024). The one exception was the leadership domain. Leadership loaded across two factors. Exploration of the indicators revealed that two distinct concepts were indeed being assessed in the survey instrument within the leadership domain. Factor one examined school mission and overall direction. Factor two measured the actual activities and evaluations of the school leadership. Since factor two measured the actual concept of leadership most closely related to the theoretical premise in this research, I used this set of items to generate the measure of leadership (Chronbach‘s α=.9103). The result of this process was the creation of a single variable that captured all of the items included in the domain measuring the appropriate underlying factors. These measures served as dependent variables in my quantitative analysis. Detailed information on the items included in each domain, along with factor loadings, and alpha levels, can be...
Dependent Variables. Tactics Each survey question regarding tactics took the following form: “In the past 2 years, how often did you organization engage in...?” Options included awareness-raising, letter writing campaigns, lobbying, filing lawsuits, sit-ins, lock-downs, demonstrations, purposeful arrests, and other civil disobedience. Available answers took the form of a Likert scale, ranging from Never (1) to Frequently (5). I employed principal component factor analysis with Varimax rotation to assess the survey items measuring tactical choices. (See Table 3.2 for full factor analysis). The ten items loaded on two factors, one indicating institutional tactics and one indicating disruptive tactics. For both, I created additive scales, standardized by the number of constituent items. The institutional tactics scale consisted of five items (Eigenvalues in parentheses): public awareness raising (.491), letter writing campaigns (.830), lobbying agencies (.883), lobbying legislators (.859), and filing lawsuits (.615). Cronbach’s Alpha is .801, indicating a high reliability for the scale. The disruptive tactics scale also consisted of five items, including sit-ins (.870), lock-downs (.849), demonstrations (.831), purposeful arrests (.853), and other civil disobedience (.817). Cronbach’s Alpha for this scale is also high, at .868. Table 3.2 Factor Analysis Factor Item Eigenvalue Cronbach’s Alpha Institutional Tactics Public Awareness Raising .491 .801 Letter Writing Campaigns .830 Lobbying Agencies .883 Lobbying Legislators .859 Filing Lawsuits .615 Disruptive Tactics Sit-Ins .870 .868 Lockdowns .849 Demonstrations .831 Purposeful Arrests .853 Other Civil Disobedience .817 QUANTITATIVE DATA ANALYSIS I used seemingly unrelated regression (SUR) to examine how the independent variables affect EJO’s tactical behaviors. Seemingly unrelated regression is appropriate here because it takes into account the non- independence of the dependent variables (Minnotte, Mannon, Stevens, and Xxxxxx 2008; Xxxx 2002). In other words, while the two types of tactics are conceptually distinct, in reality organizations often engage in both types of tactics. Seemingly unrelated regression considers the correlation among the errors between the institutional and disruptive tactics models, and uses those errors to improve the estimates (Xxxx 2002). The model also tests whether the independent variables operate differently for institutional and disruptive tactics.27 Results for seemingly unrelated regression ar...
Dependent Variables. Study participants are introduced to the ACP module with the question stem: “We now have some questions about health care planning and decisions that people may make for their end-of-life medical care.” Formal ACP is assessed with two questions: “Have you made any legal arrangements for someone to make decisions about your medical care if you become unable to make those decisions yourself? This is sometimes called a durable power of attorney for health care,” and “Do you have a living will or advance directive? These are written instructions about the type of medical treatment you would want to receive if you were unconscious or somehow unable to communicate.” I consider both outcomes separately because prior studies show that ethnic minorities are more likely than Whites adopt only one of the two strategies (Xxxx, 2011a). However, rates of overlap are very high at the population level. In the overall KN sample, 87 percent of persons with a living will also named a DPAHC, and 80 percent with a DPAHC also have a living will. End-of-life discussion is a dichotomous variable based on the question: Have you discussed with anyone plans about the types of medical treatment you want or don’t want if you become seriously ill in the future?” Those who had had a discussion were coded as 1 and those who had not were coded as 0. Persons who do not engage in each type of planning are asked their reasons for not doing so. They were provided eight closed-ended responses and could endorse as many reasons as applied. Response categories were: (1) “I do not believe this measure affects treatment,” (2) “I have not thought about my treatment preferences,” (3) “My preferences are already known to others,” (4) “I did not know this measure existed,” (5) “I do not know how to go about doing this,” (6) “My health is currently good,” (7) “I do not want to burden anyone with this responsibility,” and (8) “I do not want to think about dying and illness.” Independent Variables The key independent variable is race/ethnicity; respondents self-identify as non-Hispanic White, non-Hispanic Black, Hispanic/Latino, and Asian. Thirty nine of the original 2,150 respondents self-identified as multiracial; this cell size is too small to conduct sufficiently powered logistic regression analyses, thus they are dropped from the analytic sample. Preliminary analyses reveal that multiracial persons in the KP do not differ significantly from Whites with respect to their rates of living will completion...
