Table 2 Variables associated with adoption of CSA practices among mushroom farmers in Bangladesh as identified by bayesian logistic regression models.

From: Determinants of adoption of climate-smart agriculture (CSA) practices in mushroom farming in Bangladesh

Variables

aOR (95% HDI)

R-hat

Area

 Banagram (ref.)

1

 

 Savar Paurashava

0.48 (0.16–1.43)

1.00

 Savar

1.90 (0.69–3.82)

1.00

Educational status

 No education (ref.)

1

 

 Primary

0.88 (0.24–2.78)

1.00

 Secondary

1.53 (1.13–3.20)

1.00

Mushroom farming experience (Years)

 < 5

1

 

 5+

0.75 (0.94–1.50)

1.00

Extension visits

 No (ref.)

1

 

 Yes

1.32 (0.60–3.26)

1.00

Own land mushroom farming

 No (ref.)

1

 

 Yes

3.68 (1.76–7.34)

1.00

Knowledge about CSA practice

 No (ref.)

1

 

 Yes

3.61 (2.69–7.68)

1.00

Training about mushroom

 No (ref.)

1

 

 Yes

3.04 (1.62–5.64)

1.00

Access about climate information

 No (ref.)

1

 

 Yes

2.69 (1.33–5.51)

1.00

Access credit

 No (ref.)

1

 

 Yes

2.79 (1.06–3.46)

1.00

Knowledge about soil quality

 No (ref.)

1

 

 Yes

0.54 (0.21–1.41)

1.00

Internet

 No (ref.)

1

 

 Yes

0.76 (0.28–2.11)

1.00

Off farm job opportunity

 No (ref.)

1

 

 Yes

1.63 (0.78–2.78)

1.00

Model fitness

WAIC

 ELPD-WAIC

-59.2

 

 P-WAIC

4.9

 

 WAIC

118.4

 

LOO-CV

 ELPD-LOO

-59.2

 

 P-LOO

5.0

 

 LOOIC

118.5

 

Prediction performance

 Accuracy

0.875

 

 AUC

0.967

 
  1. ref. = Reference category.