This is shaping up to be an exciting year for both whole and lactose-free milk, two growing segments of fluid milk consumption that are poised for further gains in grocery aisles as well as Washington, D.C. policy circles.
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This article discusses the use of autoregressive integrated moving average (ARIMA) models for time series analysis. Rather than forecasting future values, we focus here on examining change across time in outcomes of interest and how this change is related to relevant variables.
Much of the data that we collect about the world around us stock prices, unemployment rates, party identification are measured repeatedly over time. By failing to account for the linked and time dependent nature of these data, common analytic techniques may misrepresent their internal structure. If we wish to describe patterns over time or forecast values beyond the observation period, we need to account for how current values may depend on previous values, trends may exist in the data, or data may vary seasonally. To visualize this, consider an electrocardiogram. The readings expected at a given moment depend not only on the preceding values but also on the position within the entire cycle. For example, follow
Objective To estimate the increase in sales of emergency contraception following the New Year’s Eve/New Year’s Day holiday.
Design Time series analysis using autoregressive integrated moving average (ARIMA) model.
Setting Traditional (that is, “bricks and mortar”) retail outlets grocery stores, drug stores, mass merchandisers, club stores, dollar stores, and military outlets in the United States from 2016 to 2022.
Data source Marketing data on weekly aggregated sales of items classified as emergency contraception gathered between 2016 and 2022 (n=362). On the basis of dates, weeks were classified as following the New Year holiday (n=6) or not (n=356).
Main outcome measure Weekly sales of levonorgestrel emergency contraception per 1000 women of reproductive age in the US population.
Results Sales of levonorgestrel emergency contraception significantly increased after the New Year holiday (0.63 (95% confidence interval 0.58 to 0.69) unit increase per 1000 women aged 15-44).