The document discusses correlation and regression analysis. Correlation measures the strength and direction of association between two continuous variables. The Pearson's correlation coefficient r ranges from -1 to 1, with values closer to these extremes indicating a stronger linear relationship. Regression finds the linear relationship between an independent and dependent variable using the regression equation y = a + bx. It can be used to predict the dependent variable from known values of the independent variable. The document provides an example of a study that used regression to analyze the relationship between fissure sealant effectiveness and exposure to fluoridated water.

1. General Studies 1 (Community dentistry 1) Lecture 8 Correlation & Regression Dr. Nizam Abdulla

5. Is there a Correlation ?

6. r = 0.98 r = 0.78 r = 0.62 r = 0.32 r = 0.08 ‘ r’ = Pearson’s Correlation Coefficient (i.e. a measure of strength of correlation)

9. Eg: We want to measure association between age and knowledge score What hypothesis ? H o : ρ = 0 ( there is no correlation between age and knowledge score ); H a : ρ ≠ 0 ( There is correlation between age and knowledge score ) (‘ ρ ’) = Population

10. The correlation (Pearson’s) between age and knowledge score is significantly different from zero ( P <.001). In other words, there is significant (linear) correlation between age and knowledge score. The observed correlation coefficient ( r ) is -.719, which suggests negative and moderate to good correlation (Colton, 1974).

11. Correlation..summary Correlation Strength of association Direction of association Any association? P-value Scatter plot Negative or positive Correlation Coefficient (r) Correlation

15. y = a + ( b * x ) Dependent = Constant + ( slope * Independent ) y = 5 + (2.5 * x ) 0,0 1 2 3 x y 5 10 15 +2.5 +2.5 +1 +1

16. Simple Linear Regression Age Knowledge Score 25 26 27 28 29 30 24 10 12 14 16 18 20 22 Slope, b is Regression Coefficient e.g . b = 1.5 means: mean knowledge score will be1.5 points more, when age is a year older.

20. An example of a research finding The effectiveness of fissure sealants in preventing caries has been well established in randomised clinical trials. However, there is less consistent evidence of fissure sealant effectiveness from community dental programs. In addition, there are unequivocal findings on the relationship between the effectiveness of fissure sealants and exposure to fluoridated water. Methods : The current cohort study examined 4–15 yr-old children across a period of between 6 mths and 3.5 yrs (mean=2 yrs). Oral health data were obtained as part of regular examinations and questionnaire data on residential and water consumption history was provided by parents or guardians. Results : A sub-group of 791 people (mean age=10.5 yrs) was selected with one contralateral pair of permanent first molars at baseline where the occlusal surface of one molar had been fissure sealed while the paired surface was diagnosed as sound. The caries incidence of the fissure sealed occlusal surfaces was 5.6% compared to 11.1% for sound surfaces (p<.001), demonstrating a 50% reduction in caries incidence for sealed vs non-sealed surfaces.

21. Children were divided into 3 categories of per cent lifetime exposure to optimally fluoridated water, 0%, 1–99% and 100%. Per cent reduction in caries increment attributable to fissure sealing increased across fluoridated water exposure categories - a 36.2% reduction was found for children with 0% exposure (p>.05), a 44.8% reduction for children with intermediate exposure (p<.01), and an 82.4% reduction for children with 100% lifetime exposure to fluoridated water (p<.001). Conclusion : The effectiveness of fissure sealants in community-based programs may be further improved when coupled with increased lifetime exposure to optimally fluoridated water.

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