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Items: 4

1.
Figure 2

Figure 2. From: Time series regression studies in environmental epidemiology.

Three alternative ways of modelling long-term patterns in the data (seasonality and trends)

Krishnan Bhaskaran, et al. Int J Epidemiol. 2013 Aug;42(4):1187-1195.
2.
Figure 1

Figure 1. From: Time series regression studies in environmental epidemiology.

Raw plots showing outcome (deaths) and exposure (ozone) data over time (London data)

Krishnan Bhaskaran, et al. Int J Epidemiol. 2013 Aug;42(4):1187-1195.
3.
Figure 3

Figure 3. From: Time series regression studies in environmental epidemiology.

Residual variation in daily deaths after ‘removing’ (i.e. modelling) season and long-term trend. Fitted values were from a spline model for season and long-term trend only (as illustrated in c)

Krishnan Bhaskaran, et al. Int J Epidemiol. 2013 Aug;42(4):1187-1195.
4.
Figure 4

Figure 4. From: Time series regression studies in environmental epidemiology.

Modelling lagged (delayed) associations between exposure and outcome. Asterisk indicates that the constraint applied was that the lagged associations for days 1 and 2 were the same, and for days 3–7 were the same

Krishnan Bhaskaran, et al. Int J Epidemiol. 2013 Aug;42(4):1187-1195.

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