Data and Methods Sample Clauses

Data and Methods. The data obtained in this study were obtained by a survey among PhD candidates at Leiden University, a large and broad research university in the Netherlands. In this section, we first describe which variables were included. Second, we expand on the survey methodology and description of respondents.

Data and Methods. To better understand couple dynamics, the DHS men’s questionnaire asks husbands about their reproductive preferences and attitudes toward family planning. For husbands in a polygynous marriage, the questions are asked for each of their wives/partners. This analysis uses DHS matched couples’ data from 14 sub-Saharan countries: Benin, Burkina Faso, Ghana, and Mali from Western Africa; Chad from central Africa; and Ethiopia, Kenya, Malawi, Mozambique, Namibia, Rwanda, Uganda, Zambia, and Zimbabwe from eastern and southern Africa. All surveys in this analysis were conducted between 1999 and 2004. The data for women are based on women age 15-49, while the data for men are based on men age 15-59 (with the exception of Kenya, Malawi, Uganda, and Zimbabwe, where the interviewed men are age 15- 54; and Benin, where the interviewed men are age 15-64). The men’s questionnaire is similar in structure to the women’s questionnaire but shorter. To the extent possible, the questions and response categories in the two questionnaires are worded identically to be comparable across countries. The section on fertility preferences includes a question on fertility intentions and ideal number of children. For fertility intentions, women and men were asked, “Would you like to have (a/another) child or would you prefer not to have any (more) children?” For ideal number of children (ideal family size), women and men were asked one of two questions, depending on whether or not they had children. Those who did not have children were asked, “If you could choose exactly the number of children to have in your lifetime, how many would that be?” Respondents who had at least one living child were asked, “If you could go back to the time you did not have children and could choose exactly the number of children to have in your lifetime, how many would that be?” In this study, a woman is defined as infecund if she had no births and no pregnancies in the past five years but has had a birth or pregnancy at some time, and has been married for the past five years but did not use contraception during that period.

Data and Methods. I conducted a cross-sectional quantitative survey with a qualitative supplement through: 120 surveys on Gichagi residents' awareness, attitudes and utilization of community health services; and a focus group discussion with 10 Gichagi community health workers assessing their views of the program.

Data and Methods. For the county level analysis, the unit of analysis is each county, and the independent variable is a binary variable that codes for whether the majority of members of each county’s elections board is white. The dependent variable is the rejection rate (in percent) of minorities in each county compared to their percentage of the voting age 10 The only county I encountered that does not have an explicitly partisan balanced board is XxXxxxxx county, which awards 4 seats to the party that received the most votes in the past general election, and 3 to the party that received the second most votes. population and registered electorate in each county. For this model, unlike the individual level model, I used data for 2014 and 2015 only. The reason for using only 2014 and 2015 is twofold. First, they are the only two complete years in the rejected data set (it contains July-December 2013 and January-July 2016). Second, 2014 accounts for 66% of all the rejections, most likely because it was an election year. Being a non-election year, 2015 serves as a good comparison to see whether registration or rejection practices change during an election year. Further, using a cross-sectional analysis simplifies this model, as the Elections Boards were constantly changing throughout the 3-year span. I collected the names of each county’s elections board members for 2013-2016, and later only used those from 2014-15. Those members from 2014 were compared only with rejections, Voting Age populations and registered voter counts from 2014—the same, respectively, for 2015. To collect the names of elections board members, I first sent an e-mail to the Secretary of State’s office asking if they had a current list of the Elections Boards for the counties. I followed this request up in-person with an elections assistant on the phone, but was told that they “would look for it,” and never heard back. I then e-mailed every county elections director and chief registrar using the contacts provided on the Secretary of State’s office website. In that e-mail I expressed that I was a student and resident of Georgia and requested the names of the board members from 2013-2016, as well as information on the appointment or elections process through which people end up on the board. From that initial e-mail I heard back from about 70 counties. It is worth noting that the information I was requesting is simply the names of current or recently serving public officials. I was not asking for any informa...

Data and Methods. In order to test the relationship between the criminalization of communities and the commodification of vulnerable bodies, this dissertation uses a quantitative research design. I first create an estimate of the number of CSEC victims in a given geography, and use these estimates as a dependent variable in structural equation models. Guided by the results of factor analysis procedures, and incorporating arguments presented and confirmed in the literature, I then estimate two latent variables: one that operationalizes the degree to which criminal justice systems are and another the degree to which immigrant communities are. I control for elements of alternative explanations for the existence of the Commercial Sex Exploitation of Children in the final models, as well as the mediating effects of anti-trafficking and runaway legislation. In this chapter, I outline the theoretical grounding for each of element of the empirical analysis, situating the methodology firmly in the extant literature, before detailing the statistical methods employed for constrained and full model analysis. Choosing the unit of analysis for this dissertation presented a number of challenges. In order to understand the relationship between the variables of interest, I sought to measure social phenomena at the community level. Insofar as greater granularity results in a better approximation of a community, ZIP codes would be ideal. There are two problems with this approach, however. First, there are no accurate demographic statistics involving criminal justice, missing persons, or public health maintained at that level. Methodologically, ZIP codes do not coordinate with neighborhoods (Grubesic 2008). Rather, they were developed to facilitate postal delivery and often cross and combine spaces that many would consider to be neighborhoods (Grubesic 2008). Thus, while giving the illusion of granularity, ZIP codes may obscure existing patterns while creating real data problems. Moving out in scope, assembling data on most variables in this study would be possible at the county level, but, as noted by Xxxxx and Targoski (2002), the crime and law data at this level are riddled with missing and underreported data. These gaps are not randomly distributed, but rather are weighted heavily towards smaller and rural counties, making county-level FBI and CDC data difficult to work with in regression models that assume errors to be randomly distributed. In order to avoid these methodological difficult...

Data and Methods. The empirical analysis will shed light on the question of whether the strength and/or direction of party stance with respect to the issue of European integration is a determinant of party electoral performance. The study concerns itself with national, legislative elections in 15 original EU member states dating from 1996-2015, depending on the timing of elections. The study proceeds to conduct linear regressions according to the five hypotheses, listed above. Hypotheses one, two, and three will be tested in two separate time periods in order to assess if the relationship in question is at all different when comparing elections held prior to 2008, and elections held in years 2008 and after. Time period A will concern elections up to 2007, time period B will concern elections from 2008 and beyond. Note that cases included in hypothesis three are limited to “mainstream” parties, as the hypothesis is concerned exclusively with mainstream party performance.4 Hypotheses four and five will be tested with separate case groups. Hypothesis four will be split according to party radicalism, running a linear regression using exclusively parties coded as “radical parties,” and again with parties coded as “mainstream parties.” Hypothesis five is 4 The study considers “mainstream parties” to be those coded as neither “radical left” nor “radical right” by the CHES dataset. split according to party ideology: Cases are divided as “Left-to-Center,” and as “Center-to- Right.”5

Data and Methods. The methodological basis of the research was constituted, first of all, by a fundamental dialectic method of cognition of the social and legal phenomena of the area under study, methods of the analysis, questionnaire survey, and also a comparative and legal method. So, comprehensive scientific approach significantly dispels the fears stated above regarding introduction of new legal institute to the Russian legislation. First of all, similar fears aren't new. Thus, according to X. Xxxxxxxx: "Obviously, this law provides certain risk. The prosecutor needs to be able to convince, intimidate, and catch criminals on a lie. Of course, there is always a probability that the defendant will begin to slander the innocent to commute the penalty. Before relying on words of the criminal, everything needs to be double-checked" [4]. The comparative and legal method is one of the fundamental means of studying of legal phenomena. Its application helps to reveal the general, special and single features of legal systems of the present days. For example, authors of this work initially proceeded from a hypothesis: introduction of institute of the pre-trial cooperation agreement to the Russian legislation in its current rudimentary state will hardly bring something new into the international legislation. The research conducted by us demonstrates a daily need of adopting foreign experience in a regulation of the studied institute. It was the topic, based on rich foreign experience that has predetermined interest in a wide range of foreign researches. Among them works of such scientists, as: Xxxxxxx X. Xxxxx [5], Xxxxxx X. Xxxxxxxxx [6], Xxxxxxxxx Xxxxx [7], Xxxxx X. Xxxxxxxxxxx [8], Xxxxxx Xxxxxx [9], Xxxx X. Xxxxxxxx [10], Xxxxxx Xxxxxx [11], Xxxxxxx X. Xxxxxxxxxx [12], Xxxx X. Xxxxxxxxx [13], and others. Having developed a special questionnaire, authors of this article have studied 20 criminal cases considered in the Supreme Court of the Republic of Tatarstan and Xxxxxxxxxxx district court of Kazan for the last 2 years (2014-2016) according to which the pre-trial cooperation agreement has been concluded with one or several defendants. Complexity combined with high scientific informational content of criminal cases predetermined the multiple volumes of the cases on the most difficult and resonant crimes committed by organized criminal groups (from 10 volumes, and more). This questionnaire comprised the following key questions: 1) at what stage of preliminary investigation petit...

Data and Methods. Data Sample Measures

Data and Methods. Below, we provide a summary of the survey methodology and measured variables. A more elaborate description of the survey questionnaire, methodology and variables is given in a working paper (Xxxxxxx, Xxxxxx, Xxxxxxxxx, xxx Xxxxxxx, & xxx xxx Xxxxxxx, 2015). The survey sample consisted of 2,193 PhD graduates who obtained a PhD from Utrecht University (a broad research university), Delft University of Technology (engineering and technology), Wageningen University (an agricultural university), or Erasmus University Rotterdam (focused on medicine and social sciences, especially economics and management) between April 2008 and March 2009 or from Leiden University (a broad research university) between January 2008 and May 2012. An invitation to the survey (which was open from 23 October 2013 until 21 January 2014) was sent through email or LinkedIn, in which the prospective respondents were informed on the purpose and content of the survey in the invitation, and strict confidentiality guaranteed, only aggregate results (impossible to trace back to individuals) to be published. Furthermore, a test of the survey showed the survey took 20 minutes to complete on average, which was also written in invitation letter, so the respondents would know which response burden to expect. In the online survey itself, the instructions made explicit it was possible to quit the survey. Up to three reminders were sent if respondents had not completed the survey. In total, 1,133 started the survey (52%), and 960 progressed to the final question (44%). Survey data were anonymized before analysis and the key to the respondents’ names and unique survey analysis ID stored in a secured folder. Non-response analysis showed that the respondents were representative of the survey set regarding gender, age, year of PhD, and city of PhD (Waaijer et al., 2015). However, Dutch nationals seemed to be overrepresented in the survey compared to the country of birth of the entire sample. In this study, we used variables on type of job, perception of career prospects, research performance and personal characteristics. Three sectors of employment were distinguished: academic R&D (dubbed academia in the paper for brevity), non-academic R&D (dubbed non-academic research) and non-R&D (dubbed outside research). The classification of respondents into these categories was based on two variables: involvement in R&D and type of employer. We follow the Organisation for Economic Co-operation and Development’s (O...

Data and Methods. Data and sample