Scotch Masking
Scotch Masking
  • Видео 79
  • Просмотров 27 244

Видео

Week11 Lecture 01 Statistical Power
Просмотров 512 года назад
Week11 Lecture 01 Statistical Power
Week11 Lecture 01 Power Analysis
Просмотров 342 года назад
Week11 Lecture 01 Power Analysis
Week07 Lecture 01 Measurement Development
Просмотров 552 года назад
Week07 Lecture 01 Measurement Development
Week07 Lecture 01 Measurement Development
Просмотров 572 года назад
Week07 Lecture 01 Measurement Development
Week07 Lecture 01 Chi Square Tests & Other Non Parametric Statistics
Просмотров 583 года назад
Week07 Lecture 01 Chi Square Tests & Other Non Parametric Statistics
Week06 Lecture 02 One Way Repeated Measures ANOVA
Просмотров 403 года назад
Week06 Lecture 02 One Way Repeated Measures ANOVA
Week06 Lecture 01 One Way Between Subjects ANOVA
Просмотров 283 года назад
Week06 Lecture 01 One Way Between Subjects ANOVA
Week05 Lecture 02 Statistical Power
Просмотров 183 года назад
Week05 Lecture 02 Statistical Power
Week05 Lecture 01 Two Sample t Tests
Просмотров 193 года назад
Week05 Lecture 01 Two Sample t Tests
Week04 Lecture 03 Matrix of Inferential Statistics
Просмотров 1193 года назад
Week04 Lecture 03 Matrix of Inferential Statistics
Week04 Lecture 02 One Sample t Test
Просмотров 873 года назад
Week04 Lecture 02 One Sample t Test
Week04 Lecture 01 Hypothesis Testing
Просмотров 223 года назад
Week04 Lecture 01 Hypothesis Testing
Week03 Lecture 02 Bivariate Linear Regression
Просмотров 203 года назад
Week03 Lecture 02 Bivariate Linear Regression
Week03 Lecture 01 Correlation
Просмотров 303 года назад
Week03 Lecture 01 Correlation
Week02 Lecture 03 Standard Scores
Просмотров 303 года назад
Week02 Lecture 03 Standard Scores
Week02 Lecture 02 Measurement Development
Просмотров 253 года назад
Week02 Lecture 02 Measurement Development
Week02 Lecture 01 Descriptive Statistics
Просмотров 343 года назад
Week02 Lecture 01 Descriptive Statistics
Week01 Lecture 03 Measurement
Просмотров 713 года назад
Week01 Lecture 03 Measurement
Week01 Lecture 02 Research Variables
Просмотров 1053 года назад
Week01 Lecture 02 Research Variables
Week01 Lecture 01 Research Foundations
Просмотров 1153 года назад
Week01 Lecture 01 Research Foundations
Week14 Assignment SPSS Principal Components & Factor Analysis Handout KEY
Просмотров 653 года назад
Week14 Assignment SPSS Principal Components & Factor Analysis Handout KEY
Week15 Lecture 01 Power Analysis
Просмотров 403 года назад
Week15 Lecture 01 Power Analysis
Week14 Lecture 01 Principal Components & Factor Analysis
Просмотров 1143 года назад
Week14 Lecture 01 Principal Components & Factor Analysis
Week12 Assignment SPSS Profile Analysis Mixed Model ANOVA Handout KEY
Просмотров 673 года назад
Week12 Assignment SPSS Profile Analysis Mixed Model ANOVA Handout KEY
Week12 Lecture 01 Profile Analysis Mixed Model ANOVA pptx
Просмотров 823 года назад
Week12 Lecture 01 Profile Analysis Mixed Model ANOVA pptx
Week11 Assignment SPSS Cox Proportional Hazards Regression Survival Analysis Handout KEY
Просмотров 1053 года назад
Week11 Assignment SPSS Cox Proportional Hazards Regression Survival Analysis Handout KEY
Week11 Lecture 01 Cox Proportional Hazards Regression Survival Analysis
Просмотров 6113 года назад
Week11 Lecture 01 Cox Proportional Hazards Regression Survival Analysis
Week10 Assignment SPSS Logistic Regression Analysis Handout KEY
Просмотров 2093 года назад
Week10 Assignment SPSS Logistic Regression Analysis Handout KEY
Week09 Lecture 01 Logistic Regression Analysis
Просмотров 1743 года назад
Week09 Lecture 01 Logistic Regression Analysis

Комментарии

  • @drcorneille9947
    @drcorneille9947 10 месяцев назад

    Very useful. Thanks for posting this video

  • @adiliomiguel5598
    @adiliomiguel5598 Год назад

    Hello! I hope you are doing well. I am currently undertaking an interrupted time series analysis for my master's thesis, focusing on comparing the impact before and after the installation of two newly added mobile harbour cranes at a terminal starting in 2022. However, I am facing difficulties as the model I have employed is not effectively capturing the underlying patterns, resulting in a poor fit. Given the importance of accuracy in prediction for my thesis, I am concerned about proceeding with a model that does not adequately capture the patterns. Thus, I am reaching out to you for your assistance in resolving this matter. I have taken several steps to address the issue, including reviewing the model specification and ensuring the inclusion of relevant predictors and interventions. However, I believe there may be additional factors or variables influencing the outcome that I may have overlooked. Consequently, I would greatly appreciate any guidance or insights you can provide in this regard. Moreover, I am open to exploring alternative model specifications to improve the fit. I understand the significance of meeting the assumptions of interrupted time series analysis, such as linearity, independence, and homoscedasticity of residuals. I have conducted initial diagnostic checks, but the poor fit persists. As this is a critical component of my research, I am eager to seek expert advice. If you have any recommendations for experts in interrupted time series analysis or statisticians who could provide guidance specific to my research context, I would be grateful Thank you in advance for considering my request for assistance. Your expertise and insights would be invaluable in helping me achieve a more accurate and reliable prediction for my master's thesis. I look forward to your response. 😟

  • @chriswong2012
    @chriswong2012 Год назад

    Thank you very much for the lecture. Very informative and useful. I really learnt a lot from that 🙏🏼🙏🏼

  • @rebeccaakunzirwe8894
    @rebeccaakunzirwe8894 Год назад

    Thanks so much! Couldn’t understand a single thing I was reading

  • @JossyMasresha
    @JossyMasresha Год назад

    thank you so much, tho i wish i had the power point presntation

  • @micahchase6995
    @micahchase6995 Год назад

    Hello, my research group really appreciates your video. We were recently introduced to the interrupted time series analysis, but we need more guidance from the faculty at our university. Would you happen to have any additional resources you can give me that I can share with my team on how to better understand the data and outputs for an interrupted time series?

  • @makhinthethtun383
    @makhinthethtun383 2 года назад

    Thank you very much for your sharing.

  • @aleenasuman2823
    @aleenasuman2823 2 года назад

    This was an amazing video- Thank you so much. How would the analysis be different if I have 2 different outcome variables to compare between 2 different groups? Do I first run the analysis for one variable for one group and then force the model for the other group for the same variable? And then repeat the same for the next variable? Or is there another way to conduct this? I hope this makes sense. Thank you so much

  • @christopherwilliams6436
    @christopherwilliams6436 2 года назад

    Excellent lecture. Very thorough. Would you please share your slides?

  • @rohayusarani924
    @rohayusarani924 2 года назад

    Hi! Thanks for the great tutorial. I am currently trying to analyze my data using interrupted time series. May i know, the model that you showed, which type of interrupted intervention pattern (step function or pulse function?). Thanks in advance!

    • @scotchmasking4270
      @scotchmasking4270 2 года назад

      This was a simple step - so it modeled a sudden-permanent effect

    • @ANGELGARCIAPEREZ-in9ox
      @ANGELGARCIAPEREZ-in9ox 5 месяцев назад

      @@scotchmasking4270 I have a question about the differentiation of the intervention variables (Driver Training - GDL Start). If you differences the intervention variables actually stop being a step variable and become a pulse variable, right? Since when you subtract the value 1 of the year 1994, for example, from the value 1 of the year 1995, the result will be 0. Thus, the Driver Training variable would have values of 0 except for the year 1990, which will have a value of 1. How should the result truly be interpreted? Could we say that Driver Training reduced by almost 7% permanently, or only during the year 1991? What would happen if we don't differentiate the intervention variable? Is this possible? Thanks for addressing these questions.

  • @utvascularendovascularandw2996
    @utvascularendovascularandw2996 2 года назад

    very good lecture

  • @jediboybetos5759
    @jediboybetos5759 2 года назад

    Thank you for this

  • @martinasharp7495
    @martinasharp7495 2 года назад

    Thank you for your generosity in sharing this.

  • @MachaLeingakoa
    @MachaLeingakoa 2 года назад

    Sir i am doing a training of yoga vs aerobic in 20 traineers each with no control groups . I measure the progress after every 4 weeks for 12 weeks . Can i still used this ANCOVA methods as statistic

  • @laurawharton8726
    @laurawharton8726 3 года назад

    This is really useful, thank you! How do you force SPSS to show one of the variables in the model output even if it was non-significant?

  • @tsetsegeesambuu3139
    @tsetsegeesambuu3139 3 года назад

    Thank you very much, I learned a lot