By Hideo Kusuoka and Julien I.E. Hoffman
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Extra resources for Advice on Statistical Analysis for Circulation Research
They have been coded as follows: Christian Jew Hindu Muslim 1 2 3 4 The numbering is arbitrary, the four religions could have been put in a diﬀerent order and diﬀerent numbers could have been assigned to them. This variable can be transformed into four dummy variables: Christian, Jew, Hindu, Muslim. A Christian would be coded 1 on the variable Christian and 0 on Jew, Hindu and Muslim. A Jew would be coded 0 on the variable Christian, 1 on Jew and 0 on Hindu and Muslim. Similarly a Hindu would be coded 1 on Hindu and 0 on the other three and a Muslim 1 on Muslim and 0 on the other three variables.
Conﬁdence intervals are related to signiﬁcant tests. The purpose of the signiﬁcance test was to ﬁnd evidence to reject the null hypothesis, b = 0. 96) we would reject the null hypothesis and conclude that b was not equal to 0. We can then estimate a 95% conﬁdence interval around b. In this situation the 95% conﬁdence interval would not contain the value 0; because if the probability is less than 5% that b is 0 then we can be 95% sure that whatever range b lies within, 0 will not be in that range.
1b) reduces to: Row total × Column total Total sample which is the formula given in introductory statistics texts for calculating the expected values when calculating the chi-squared test of association for two-way tables. 1a) has advantages which we will come to appreciate when loglinear models are described in Chapter 7. 77 = 573 This formula can be applied to each cell of the table by suitably adapting the row and column marginal probabilities depending on which row and column the cell falls.