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J. MARSHALL the different tests were well designed, and measured different aspects of the speaker’s language use as they were intended to. ssscor phov 0.886 PHOVARSSSCOR 1.2 1 0.8 SSSCOR 0.6 SSSCOR 0.4 0.2 0 0 10 20 30 40 50 60 lexrec phov 0.794 PHOVAR PHOVARLEXREC 60 50 40 LEXREC 30 LEXREC 20 10 0 0 10 20 30 40 50 60 PHOVAR The effect of sex is not important for this study either, and will be removed during model building. The summary statistics show that AGE is a strong predictor of dialect use, while SEX has less of an effect, although males do use the dialect more than females. Next we will use more advanced methods to ‘flatten’ the effects of age and sex on the language use of the speakers, and then see whether the social variables identified have a significant effect on their own. 164
SOCIAL NETWORKS IN A RURAL SETTING 7.2. Regression Analysis: Building a Model Using linear regression analyses, we will build a model that adds first age, then sex, then the interaction between age and sex into the equation. After that, the relevant social variables will be added in order to test their significance as predictors of language use. The two results to take note of are: 1) The P-value (probability of the variation occurring by chance), the lower this figure the more significant the result. The minimum accepted for most studies is 0.05 (or 5% possibility of the variation occurring by chance). 2) The (adjusted) r-squared value, a measure of how much of the variation in the dependent variable is accounted for by the independent variable(s). First we will test LIFMOD, the index score for degree of mental urbanisation, as a predictor of PHOVAR, the first of the linguistic scores, which was achieved by means of the picture list. First, the variable AGE will be entered, and the output examined. Next, the variable SEX will be entered, then the variable AGE x SEX, and finally, the predictor variable LIFMOD. This has the effect of ‘smoothing out’ the effect of the first three, and testing the last as a predictor of dialect maintenance. Simply finding that the oldest people in the community speak the dialect the most, or that men use the dialect more than women is not surprising. The research question requires that we find out which, if any, of the other social variables predict language maintenance. 7.3. LIFMOD as a Predictor of PHOVAR The regression equation is PHOVAR = 18.2 + 0.569 AGE Predictor Coef StDev T P Constant 18.168 2.625 6.92 0.000 AGE 0.56890 0.06742 8.44 0.000 S = 11.69 R-Sq = 53.9% R-Sq(adj) = 53.1% The P value is highly significant, and the adjusted r-squared value is reasonable. This confirms that AGE is a strong predictor of dialect use. Next we add the variable SEX: 165
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K ALJENAIE testing ground. To what
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K ALJENAIE Motar, A. (1969). Khasai
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P. COUTSOUGERA References Anderson,
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R. INGHAM cognitive deficits. They
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R. INGHAM 2. Subjects and hypothese
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S. KULKARNI in the Indian caste hie
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S. KULKARNI The main study includes
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S. KULKARNI 4. Quantitative Analyse
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S. KULKARNI comparatively lower (in
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S. KULKARNI Table 3: Percentage use
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S. KULKARNI showing an almost compl
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S. KULKARNI 50 mean % std. score 40
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Page 124 and 125: S. KULKARNI Bapuji, B.R. (1994).
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Page 128 and 129: J. MARSHALL 2. Change versus Resist
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