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Understanding Common Study Results            Foundations I         September 28, 2011
Studies and Evidence         Many studies include statistical analysis         Though there is a rigorous review process...
Objectives             Interpret Confidence Intervals             Define dependent vs. independent variables            ...
Structured Arguments           Claim – Statement that the researcher makes           Data – The source on which they bas...
Obesity & Preschoolers        Objective: Our objective was to determine the association between        physical activity a...
Data                 Always look for descriptive                 statistics                 These will help you determine ...
Warranting – Explicating what they did        “inclusion criteria for the analyses were: completion of 4.5 days of activit...
      When odds are close to 1 that            means event is equally likely            in both groups           When od...
Whats dependent whats Independent?        Using general linear model regression and adjusting for age, sex, and        rac...
Differences Between Boys & Girls2011-2012                 10
Another Way to Check for Differences         Chi-Squares Goodness of fit test would help us to          determine if we h...
IS This Study Important?        “Although we hypothesized that children who were more        sedentary would have a higher...
Contact         Dr. Saad Chahine              Saad.Chahine@msvu.ca2011-2012                     13
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Chahine Understanding Common Study Results

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Understanding Common Study Results

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Chahine Understanding Common Study Results

  1. 1. Understanding Common Study Results Foundations I September 28, 2011
  2. 2. Studies and Evidence  Many studies include statistical analysis  Though there is a rigorous review process The following could happen: 1. An inappropriate analysis or results slips thorugh. 2. An approach used is out dated. 3. An claim being made is not-logical.2011-2012 2
  3. 3. Objectives  Interpret Confidence Intervals  Define dependent vs. independent variables  Interpret results from t-tests, chi-square analysis and regression analysis  Differentiate statistical from clinical significance2011-2012 3
  4. 4. Structured Arguments  Claim – Statement that the researcher makes  Data – The source on which they base this statement  Warrant  Backing  Rebuttal – what are the holes you find  Qualifier – Is the confidence interval  Toulmin, S. (1958). The Uses of Argument. Cambridge: Cambridge University Press.2011-2012 4
  5. 5. Obesity & Preschoolers Objective: Our objective was to determine the association between physical activity and BMI among racially diverse low-income preschoolers. Discussion: This study suggests that, in a diverse group of preschoolers, vigorous and very vigorous activity are associated with lower odds of overweight. However, these findings require corroboration in a diverse sample of preschoolers using a longitudinal design. Metallinos-Katsars, S.E., Freedson, S. P., Fulton, E.J., & Sherry, B. (2007). The association between an objective measure of physical activity and weight status in preschoolers. Obesity, 15, 686-694.2011-2012 5
  6. 6. Data Always look for descriptive statistics These will help you determine the sample how much inference you can make based on this data.2011-2012 6
  7. 7. Warranting – Explicating what they did “inclusion criteria for the analyses were: completion of 4.5 days of activity assessment (27) and measurement of height and weight within the following time frame of the activity assessment: 1) children 24 to 35.99 months old: within 90 days, 2) children 36 to 59.99 months old: within 120 days. These time frames were based on the magnitude of growth velocity for the aforementioned ages (28,29). Twenty-three children (27.4%) did not complete at least 4.5 days of activity assessment and three (3.6%) did not have height and weight measured within the specified time frame. Two (2.4%) were excluded because they were 24 months old, precluding the calculation of BMI percentile for age. Thus, the final analytic sample included 56 children(66.7%).”2011-2012 7
  8. 8.  When odds are close to 1 that means event is equally likely in both groups  When odds are greater than 1 it means its in favor of the first group  When odds are less than one odds are in favor of the other group  95% confident that the true odds ratio is between XX & XX  p-value 0.05 “The effect being by chance”2011-2012 8
  9. 9. Whats dependent whats Independent? Using general linear model regression and adjusting for age, sex, and race/ethnicity, those classified as overweight had significantly lower mean daily very vigorous minutes (4.6 mins vs. 2.6 mins, p 0.05) and lower mean daily total very active minutes (32.1 min vs. 22.9 mins, p 0.04) than normal- weight children. Adjusting for the time that the monitor was worn per day did not substantially alter the magnitude of the group differences. -Examined overweight status (dependent) on Activity, Age, Sex, Race - In univariate analysis you will always have one dependent variable, and potentially multiple independent variables the idea is to examine relationship, strength and direction of relationship2011-2012 9
  10. 10. Differences Between Boys & Girls2011-2012 10
  11. 11. Another Way to Check for Differences  Chi-Squares Goodness of fit test would help us to determine if we have approximately a balances sample 50% boys 50% girls if p>0.05 then sample doesn’t differ from assumed  When you want to compare two categorical variables then you need chi-squares test which also produces a p-value eg. Sex & Being Vigorously Active2011-2012 11
  12. 12. IS This Study Important? “Although we hypothesized that children who were more sedentary would have a higher risk of overweight, we did not find significant associations between light activity or even a sedentary pattern of physical activity and overweight. One explanation may be the small sample size of this study, which limited statistical power.” - Clinical significance VS Statistical significance2011-2012 12
  13. 13. Contact  Dr. Saad Chahine Saad.Chahine@msvu.ca2011-2012 13

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