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The slope of the pressure-natriuresis relationship was less steep in patients who carried both minor alleles (AG/GG for rs3790261 and GA/AA for rs11893826; 0.031±0.005 µEq/mmHg/min ± se) than in those carrying the remaining genotype combinations (0.010±0.002 µEq/mmHg/min ± se) (p interaction = 1.55E-04, p model = 3.35E-05 in dummy analysis).
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Copies of the deals are handed out afterward that include Deep Finesse double-dummy analysis.
### All variables in coded as dummy for analysis.
This could not be achieved via conventional methods (eg, dummy regression analysis).
The simplest and most common way of creating variables to represent categories is known as dummy variable analysis [ 13].
Inserting province as dummy variables into analysis is equivalent to using a fix-effect model, where provincial dummies capture variations in health care utilizations between provinces [ 18].
In the first analysis, dummy variables were used for missing data, with creation of a categorical indicator for missing responses (missing category) (see online supplementary appendix table S1).
(We also try using lagged values of the children dummy in the analysis without observing any material changes in the weight estimates).
To allow all observations to be used in estimating the effect of non-missing observations in the analysis, dummy values were generated for the missing observations of each variable.
To test whether place of birth is associated differently with satisfaction in the two countries, we included three interaction terms, one for each dummy, in our analysis but retained only the significant term, which is "hospital after referral*country".
For cross-tabulation and logistic regression analysis, dummy variables were constructed yielding the categories (1) "at least several times a week", and (0) "rarely/never" with respect to consumption of sugared snacks and drinks.
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