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Table 4 Characteristics of the basic methodological considerations (autocorrelation, non-stationarity, seasonality) (Only for ITS with aggregated unit)

From: Design and statistical analysis reporting among interrupted time series studies in drug utilization research: a cross-sectional survey

Characteristics

n

%

Considered all of three methodological issues (autocorrelation, non-stationarity and seasonality) (N = 149)

 Yes

14

9.4

Considered at least one of three methodological issues (N = 149)

 Yes

117

78.5

Autocorrelation

Autocorrelation acknowledged (N = 149)

  Yes

108

72.5

Autocorrelation acknowledged (ITS study used ARIMA model) (N = 24)

 Yes

20

83.3

Autocorrelation acknowledged (ITS study used Non-ARIMA model) (N = 125)

 Yes

88

70.4

Autocorrelation identified methods (N = 108)

 Durbin Watson test

40

37.0

 ACF

9

8.3

 Cumby-Huizinga test

5

4.6

 Ljung-Box2 test

3

2.8

 Others a

4

3.7

 Not reported

47

43.5

Adjusted for autocorrelation (N = 108)

 Yes

65

60.2

 No adjustment for autocorrelation (after statistical test)

16

14.8

 Unclear

27

25.0

If yes, which method was used? (N = 65)

 ARIMA

31

47.7

 GLS

16

24.6

 OLS with Newey-West standard errors

12

18.5

 Add lag terms

5

7.7

 Generalized Estimating Equation

1

1.5

Non-stationarity

Non-stationarity acknowledged (N = 149)

  Yes

20

13.4

Non-stationarity acknowledged (ITS study used ARIMA model) (N = 24)

 Yes

11

45.9

Non-stationarity acknowledged (ITS study used Non-ARIMA model) (N = 125)

 Yes

9

7.2

Non-stationarity identified methods (N = 20)

 Augmented Dickey-Fuller test

8

40.0

 Plot the raw data

1

5.0

 Not reported

11

55.0

Adjusted for non-stationarity (N = 20)

 Yes

15

75.0

 No adjustment for non-stationarity (after statistical test)

4

20.0

 Unclear

1

5.0

If yes, which method was used? (N = 15)

 ARIMA

11

73.3

 Others b

4

26.7

Seasonality

Seasonality acknowledged (N = 149)

  Yes

60

40.3

Seasonality acknowledged (ITS study used ARIMA model) (N = 24)

 Yes

15

62.5

Seasonality acknowledged (ITS study used Non-ARIMA model) (N = 125)

 Yes

45

36.0

Seasonality identified methods (N = 60)

 Augmented Dickey-Fuller test

4

6.7

 Plot the raw data

3

5.0

 Others c

6

10.0

 Not reported

47

78.3

Adjusted for seasonality (N = 60)

 Yes

41

68.3

 No adjustment for seasonality (after statistical test)

9

15.0

 Unclear

10

16.7

If yes, which method was used? (N = 41)

 Add seasonality terms

18

43.9

 ARIMA

13

31.7

 Fourier function

8

19.5

 Othersd

2

4.9

  1. aOthers included residual plots (2 studies), Bartlett formula (1 study), Breusch-Godfrey test (1 study)
  2. bOthers included add dummy variable (3 studies) and first difference (1 study)
  3. cOthers included Cumby-Huizinga test (1 study), Kruskal–Wallis test (1 study), Webel-Ollech overall seasonality (1 study), Summary statistics (1 study), add seasonality terms (1 study), test lagged correlation (1 study)
  4. dOthers included Holt-Winters seasonal smoothing approach (1 study) and Lag period (1 study)