New Zealand Attitudes And Values Study
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New Zealand Attitudes And Values Study
The New Zealand Attitudes and Values Study (NZAVS) is a longitudinal study conducted in New Zealand. The NZAVS was started in 2009 by Chris Sibley, a professor in psychology at the University of Auckland. The NZAVS was inspired by major social surveys conducted internationally, such as the National Election Studies, the World Values Survey and the General Social Survey, and aims to provide a similar resource for New Zealand. As of November 8, 2016, the NZAVS research team had published 100 peer reviewed publications using data from the study. Sample details Questionnaires The NZAVS uses a self-report inventory to collect information. The questionnaire is administered via both postal mail and an online survey. The NZAVS includes a large range of scales including those measuring self-esteem, national and personal wellbeing, satisfaction with life, religious beliefs, personality, psychological distress, ideologies, political and environmental attitudes. Data structure The NZ ...
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Longitudinal Study
A longitudinal study (or longitudinal survey, or panel study) is a research design that involves repeated observations of the same variables (e.g., people) over short or long periods of time (i.e., uses longitudinal data). It is often a type of observational study, although it can also be structured as longitudinal randomized experiment. Longitudinal studies are often used in social-personality and clinical psychology, to study rapid fluctuations in behaviors, thoughts, and emotions from moment to moment or day to day; in developmental psychology, to study developmental trends across the life span; and in sociology, to study life events throughout lifetimes or generations; and in consumer research and political polling to study consumer trends. The reason for this is that, unlike cross-sectional studies, in which different individuals with the same characteristics are compared, longitudinal studies track the same people, and so the differences observed in those people are less l ...
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Political
Politics (from , ) is the set of activities that are associated with making decisions in groups, or other forms of power relations among individuals, such as the distribution of resources or status. The branch of social science that studies politics and government is referred to as political science. It may be used positively in the context of a "political solution" which is compromising and nonviolent, or descriptively as "the art or science of government", but also often carries a negative connotation.. The concept has been defined in various ways, and different approaches have fundamentally differing views on whether it should be used extensively or limitedly, empirically or normatively, and on whether conflict or co-operation is more essential to it. A variety of methods are deployed in politics, which include promoting one's own political views among people, negotiation with other political subjects, making laws, and exercising internal and external force, includ ...
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Joseph Bulbulia
Joseph A. Bulbulia is a Professor of Psychology in the Faculty of Science at Victoria University of Wellington (2020-present). He was the Maclaurin Goodfellow Chair in the School of Humanities, Faculty of Arts at University of Auckland (2018-2020). He previously served as a Professor in the School of Art History, Classics and Religious Studies at Victoria University of Wellington (2000– 2017). Bulbulia is regarded as one of the founders of the contemporary evolutionary religious studies . He is a past president of the International Association for the Cognitive Science of Religion and is currently co-editor of Religion, Brain & Behavior. Bulbulia is one of four on the Senior Management Team of the New Zealand Attitudes and Values Study, a 20-year longitudinal study tracking over 15,000 New Zealanders each year. He is an associate investigator for Pulotu, a database of 116 Pacific cultures purpose-built to investigate the evolutionary dynamics of religion. In 2016 Bulbulia won a ...
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Multilevel Model
Multilevel models (also known as hierarchical linear models, linear mixed-effect model, mixed models, nested data models, random coefficient, random-effects models, random parameter models, or split-plot designs) are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains measures for individual students as well as measures for classrooms within which the students are grouped. These models can be seen as generalizations of linear models (in particular, linear regression), although they can also extend to non-linear models. These models became much more popular after sufficient computing power and software became available. Multilevel models are particularly appropriate for research designs where data for participants are organized at more than one level (i.e., nested data). The units of analysis are usually individuals (at a lower level) who are nested within contextual/aggregate units (at a higher le ...
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Mixture Model
In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that represents the probability distribution of observations in the overall population. However, while problems associated with "mixture distributions" relate to deriving the properties of the overall population from those of the sub-populations, "mixture models" are used to make statistical inferences about the properties of the sub-populations given only observations on the pooled population, without sub-population identity information. Mixture models should not be confused with models for compositional data, i.e., data whose components are constrained to sum to a constant value (1, 100%, etc.). However, compositional models can be thought of as mixture models ...
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Structural Equation Modeling
Structural equation modeling (SEM) is a label for a diverse set of methods used by scientists in both experimental and observational research across the sciences, business, and other fields. It is used most in the social and behavioral sciences. A definition of SEM is difficult without reference to highly technical language, but a good starting place is the name itself. SEM involves the construction of a '' model'', to represent how various aspects of an observable or theoretical phenomenon are thought to be causally structurally related to one another. The '' structural'' aspect of the model implies theoretical associations between variables that represent the phenomenon under investigation. The postulated causal structuring is often depicted with arrows representing causal connections between variables (as in Figures 1 and 2) but these causal connections can be equivalently represented as equations. The causal structures imply that specific patterns of connections should ap ...
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Bayesian Linear Regression
Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables, with the goal of obtaining the posterior probability of the regression coefficients (as well as other parameters describing the distribution of the regressand) and ultimately allowing the out-of-sample prediction of the regressand (often labelled y) '' conditional on'' observed values of the regressors (usually X). The simplest and most widely used version of this model is the ''normal linear model'', in which y given X is distributed Gaussian. In this model, and under a particular choice of prior probabilities for the parameters—so-called conjugate priors—the posterior can be found analytically. With more arbitrarily chosen priors, the posteriors generally have to be approximated. Model setup Consider a standard linear regression problem, in which for i = 1, \ldots, n we specify the mean of the conditional distribution o ...
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Latent Growth Modeling
Latent growth modeling is a statistical technique used in the structural equation modeling (SEM) framework to estimate growth trajectories. It is a longitudinal analysis technique to estimate growth over a period of time. It is widely used in the field of psychology, behavioral science, education and social science. It is also called latent growth curve analysis. The latent growth model was derived from theories of SEM. General purpose SEM software, such as OpenMx, lavaan (both open source packages based in R), AMOS, Mplus, LISREL, or EQS among others may be used to estimate growth trajectories. Background Latent Growth Models Tucker, L.R. (1958) Determination of parameters of a functional relation by factor analysis. ''Psychometrika'' 23, 19-23. Rao, C.R. (1958) Some statistical methods for the comparison of growth curves. ''Biometrics''. 14, 1-17. Scher, A.M., Young, A.C. & Meredith, W.M. (1960) Factor analysis of the electrocardiogram. ''Circulation Research'' 8, 519-526. ...
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Quantitative Study
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies. Associated with the natural, applied, formal, and social sciences this research strategy promotes the objective empirical investigation of observable phenomena to test and understand relationships. This is done through a range of quantifying methods and techniques, reflecting on its broad utilization as a research strategy across differing academic disciplines. The objective of quantitative research is to develop and employ mathematical models, theories, and hypotheses pertaining to phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. Quantitative data is any data that is i ...
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Statistics New Zealand
Statistics New Zealand ( mi, Tatauranga Aotearoa), branded as Stats NZ, is the public service department of New Zealand charged with the collection of statistics related to the economy, population and society of New Zealand. To this end, Stats NZ produces censuses and surveys. Organisation Statistics New Zealand employs people with a variety of skills, including statisticians, mathematicians, computer science specialists, accountants, economists, demographers, sociologists, geographers, social psychologists, and marketers. There are seven organisational subgroups each managed by a Deputy Government Statistician: * Macro-economic and Environment Statistics studies prices, national accounts, develops macro-economic statistics, does government and international accounts, and ANZSIC 06 implementation (facilitating changeover to new classification code developed jointly with Australian statistics officials.) * Social and Population Statistics studies population, social conditions, ...
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