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Keywords: SEM 

  • Structural Equation Modelling using Stata: Online

    28 - 29 October 2022

    Structural Equation Modelling using Stata: Online https://dresa.org.au/events/structural-equation-modelling-using-stata-online This course is designed for participants with an introductory-level understanding of the statistical methods of regression analysis and exploratory factor analysis. Participants will experience hands-on SEM examples and have the ability to build their own Stata SEM models. This workshop is targeted at those researchers who wish to expand their understanding of this highly powerful technique. SEM has been utilised in many areas of research from psychology to medicine. 2022-10-28 09:00:00 UTC 2022-10-29 17:00:00 UTC ACSPRI ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Structural equation modellingSEMStatisticsSTATA
  • Fundamentals of Structural Equation Modelling: Online

    16 - 20 January 2023

    Fundamentals of Structural Equation Modelling: Online https://dresa.org.au/events/fundamentals-of-structural-equation-modelling-online Structural equation modelling—or structural equations with latent variables—is a very general statistical model and widely used method. For example, SEM is used in fundamental disciplines such as the social, economic and psychological sciences, the biological sciences, and applied disciplines such as education, health and marketing. SEM has become popular for several reasons, apart from its generality: (i) all SEM models can be represented visually, (ii) a standard notation helps researchers to communicate, and (iii) several software packages for estimating SEM models are readily available (e.g., AMOS, LISREL, Mplus, R). This course provides an overview of the fundamentals of SEM. As well as the statistical theory, an overview of the many applications and capabilities of SEM is given. The course is not particularly mathematical, but instead places emphasis on the fundamental concepts of SEM and how it is used by applied researchers. General aims of the course are for students to develop a readiness for using SEM software and to develop the requisite knowledge for applying SEM methods and models in an intelligent way. Note that participants may be invited to briefly present their own research on the last day of class. This exercise, along with the formal lecture material, might help participants to chart a direction forward in their study and application of SEM. 2023-01-16 10:00:00 UTC 2023-01-20 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all SEMStructural equation modellingStatistical Methodsquantitative
  • Multi-level Analysis using Mplus: Online

    16 - 20 January 2023

    Multi-level Analysis using Mplus: Online https://dresa.org.au/events/multi-level-analysis-using-mplus-online This course is designed as an introduction to the concepts and techniques required to analyse data that is multi-level in nature. (That is, data that is derived from subjects who are nested within groups or data that involves repeated measures that are nested within subjects) In conventional regression analysis it is assumed that subjects are randomly selected and, therefore, all the variance in your dependent variables is due solely to variation amongst individuals. However, in most studies, subjects are clustered within a group and multiple groups are sampled. For example, in an education study, we may have students clustered within multiple classes; in a human resourcing study, we may have employees clustered within multiple work units or teams. In such sampling, although some of the variance in your dependent variables will be due to variation amongst individuals, some the variance in your dependent variables will also be due to variation amongst the groups themselves. In such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. Repeated measure designs should also be analysed using multilevel analysis because the repeated observations are nested within subjects. For example, in a marketing study, we may have repeated measures of consumers’ attitudes to a brand over the life of a marketing campaign; in an epidemiology study, we may have repeated measures of a health outcome over the life of a drug treatment regime. In such studies, although some of the variance in your dependent variables will be due to variation across the various time occasions, some the variance in your dependent variables will also be due to variation amongst individuals themselves. Again, in such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. 2023-01-16 10:00:00 UTC 2023-01-20 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all multilevel modellingSEMStatistical MethodsStatistics
  • Advanced Structural Equation Modelling: Online

    6 - 10 February 2023

    Advanced Structural Equation Modelling: Online https://dresa.org.au/events/https-www-acspri-org-au-summer-program-2023-advanced-structural-equation-modelling-online Introductory courses typically cover path analysis amongst observed variables, confirmatory factor analysis, and full SEM models with latent variables. This course covers a number of more complex models including models with mediating variables, models with interactions (moderation), ANOVA and ANCOVA models for latent outcomes, multi-level models (including repeated measures models) and mixture models. Furthermore, introductory courses usually deal only with continuous, normally distributed variables. This course addresses the treatment of non-normal data and covers the analysis of observed categorical variables including ordered categorical (ordinal) variables such as Likert scales and unordered categorical (nominal) variables that may be binary (Male/Female, Problem Gambler/Non Gambler, Smoker/Non-Smoker, etc.) or polynomial (Australian/Indonesian/South African, etc.) Detailed notes with worked examples and references will be provided as a basis for both the lecture and hands-on computing aspect of the course. The target audience for this course is existing AMOS and/or Mplus users. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Structural equation modellingAdvancedSEMMplusAMOS
  • Structural Equation Modelling using Stata: Online

    28 - 29 October 2022

    Structural Equation Modelling using Stata: Online https://dresa.org.au/events/structural-equation-modelling-using-stata-online This course is designed for participants with an introductory-level understanding of the statistical methods of regression analysis and exploratory factor analysis. Participants will experience hands-on SEM examples and have the ability to build their own Stata SEM models. This workshop is targeted at those researchers who wish to expand their understanding of this highly powerful technique. SEM has been utilised in many areas of research from psychology to medicine. 2022-10-28 09:00:00 UTC 2022-10-29 17:00:00 UTC ACSPRI ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Structural equation modellingSEMStatisticsSTATA
  • Fundamentals of Structural Equation Modelling: Online

    16 - 20 January 2023

    Fundamentals of Structural Equation Modelling: Online https://dresa.org.au/events/fundamentals-of-structural-equation-modelling-online Structural equation modelling—or structural equations with latent variables—is a very general statistical model and widely used method. For example, SEM is used in fundamental disciplines such as the social, economic and psychological sciences, the biological sciences, and applied disciplines such as education, health and marketing. SEM has become popular for several reasons, apart from its generality: (i) all SEM models can be represented visually, (ii) a standard notation helps researchers to communicate, and (iii) several software packages for estimating SEM models are readily available (e.g., AMOS, LISREL, Mplus, R). This course provides an overview of the fundamentals of SEM. As well as the statistical theory, an overview of the many applications and capabilities of SEM is given. The course is not particularly mathematical, but instead places emphasis on the fundamental concepts of SEM and how it is used by applied researchers. General aims of the course are for students to develop a readiness for using SEM software and to develop the requisite knowledge for applying SEM methods and models in an intelligent way. Note that participants may be invited to briefly present their own research on the last day of class. This exercise, along with the formal lecture material, might help participants to chart a direction forward in their study and application of SEM. 2023-01-16 10:00:00 UTC 2023-01-20 17:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all SEMStructural equation modellingStatistical Methodsquantitative
  • Multi-level Analysis using Mplus: Online

    16 - 20 January 2023

    Multi-level Analysis using Mplus: Online https://dresa.org.au/events/multi-level-analysis-using-mplus-online This course is designed as an introduction to the concepts and techniques required to analyse data that is multi-level in nature. (That is, data that is derived from subjects who are nested within groups or data that involves repeated measures that are nested within subjects) In conventional regression analysis it is assumed that subjects are randomly selected and, therefore, all the variance in your dependent variables is due solely to variation amongst individuals. However, in most studies, subjects are clustered within a group and multiple groups are sampled. For example, in an education study, we may have students clustered within multiple classes; in a human resourcing study, we may have employees clustered within multiple work units or teams. In such sampling, although some of the variance in your dependent variables will be due to variation amongst individuals, some the variance in your dependent variables will also be due to variation amongst the groups themselves. In such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. Repeated measure designs should also be analysed using multilevel analysis because the repeated observations are nested within subjects. For example, in a marketing study, we may have repeated measures of consumers’ attitudes to a brand over the life of a marketing campaign; in an epidemiology study, we may have repeated measures of a health outcome over the life of a drug treatment regime. In such studies, although some of the variance in your dependent variables will be due to variation across the various time occasions, some the variance in your dependent variables will also be due to variation amongst individuals themselves. Again, in such cases, multilevel analysis (MLA) should be employed to account for the different levels of variation. 2023-01-16 10:00:00 UTC 2023-01-20 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all multilevel modellingSEMStatistical MethodsStatistics
  • Advanced Structural Equation Modelling: Online

    6 - 10 February 2023

    Advanced Structural Equation Modelling: Online https://dresa.org.au/events/https-www-acspri-org-au-summer-program-2023-advanced-structural-equation-modelling-online Introductory courses typically cover path analysis amongst observed variables, confirmatory factor analysis, and full SEM models with latent variables. This course covers a number of more complex models including models with mediating variables, models with interactions (moderation), ANOVA and ANCOVA models for latent outcomes, multi-level models (including repeated measures models) and mixture models. Furthermore, introductory courses usually deal only with continuous, normally distributed variables. This course addresses the treatment of non-normal data and covers the analysis of observed categorical variables including ordered categorical (ordinal) variables such as Likert scales and unordered categorical (nominal) variables that may be binary (Male/Female, Problem Gambler/Non Gambler, Smoker/Non-Smoker, etc.) or polynomial (Australian/Indonesian/South African, etc.) Detailed notes with worked examples and references will be provided as a basis for both the lecture and hands-on computing aspect of the course. The target audience for this course is existing AMOS and/or Mplus users. 2023-02-06 10:00:00 UTC 2023-02-10 16:00:00 UTC ACSPRI Online, Australia Online Australia ACSPRI info@acspri.org.au [] [] 12 workshop open_to_all Structural equation modellingAdvancedSEMMplusAMOS

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