Table 2. Open in new tab Within and...

Variables

(path)

Est.

p^a

[95% CI]^b

Within

OS_ij

→

CA_ij

(aw1)

.244

.017

.000

[.210, .277]*

SMK_{i(j → j + 1)}

(c'w1)

.101

.029

.000

[.039, .153]*

SA_ij

→

CA_ij

(aw2)

.264

.010

.000

[.245, .283]*

SMK_{i(j → j+1)}

(c'w2)

.087

.017

.000

[.056, .118]*

CA_ij

→

SMK_{i(j → j+1)}

(bw)

.396

.013

.000

[.372, .423]*

SMK_{i(j-1 → j)}

→

SMK_{i(j → j+1)}

(ar1)

.344

.019

.000

[.307, .375]*

OS_ij

.032

.002

.000

[.028, .035]*

SA_ij

.102

.005

.000

[.092, .110]*

CA_ij

.360

.006

.000

[.350, .371]*

OS_ij

with

SA_ij

.040

.001

.000

[.038, .042]*

Between

SES_i

→

OS_i

(ab1)

−.027

.006

.000

[−.039, −.015]*

SA_i

(ab2)

−.046

.017

.001

[−.084, −.016]*

CA_i

(ab3)

−.085

.039

.017

[−.155, −.007]*

SMK_i

(c'b)

−.064

.033

.025

[−.127, .001]

OS_i

→

CA_i

(ab4)

1.126

.353

.000

[.457, 1.849]*

SMK_i

(bb1)

−.048

.286

.431

[−.597, .514]

SA_i

→

CA_i

(ab5)

.900

.122

.000

[.688, 1.160]*

SMK_i

(bb2)

.267

.107

.005

[.058, .460]*

CA_i

→

SMK_i

(bb3)

.287

.043

.000

[.201, .370]*

OS_i

with

SA_i

.024

.006

.000

[.012, .034]*

Latent Variable^c

SES_i

→

Income_i

1.000

.000

[1.000, 1.000]

College_i

.374

.075

.000

[.233, .531]*

Insured_i

.817

.314

.000

[.487, 1.552]*

Employed_i

.466

.085

.000

[.303, .641]*

Table 2.

Open in new tab

Within and between estimates from a multilevel structural equation model of socioeconomic status (SES), exposure to other smokers (OS), exposure to places where smoking is allowed (SA), cigarette availability (CA), and smoking lapse (SMK)

Variables			(path)	Est.	SD	p^a	[95% CI]^b
Within
OS_ij	→	CA_ij	(aw1)	.244	.017	.000	[.210, .277]*
		SMK_{i(j → j + 1)}	(c'w1)	.101	.029	.000	[.039, .153]*
SA_ij	→	CA_ij	(aw2)	.264	.010	.000	[.245, .283]*
		SMK_{i(j → j+1)}	(c'w2)	.087	.017	.000	[.056, .118]*
CA_ij	→	SMK_{i(j → j+1)}	(bw)	.396	.013	.000	[.372, .423]*
SMK_{i(j-1 → j)}	→	SMK_{i(j → j+1)}	(ar1)	.344	.019	.000	[.307, .375]*
		OS_ij		.032	.002	.000	[.028, .035]*
		SA_ij		.102	.005	.000	[.092, .110]*
		CA_ij		.360	.006	.000	[.350, .371]*
OS_ij	with	SA_ij		.040	.001	.000	[.038, .042]*
Between
SES_i	→	OS_i	(ab1)	−.027	.006	.000	[−.039, −.015]*
		SA_i	(ab2)	−.046	.017	.001	[−.084, −.016]*
		CA_i	(ab3)	−.085	.039	.017	[−.155, −.007]*
		SMK_i	(c'b)	−.064	.033	.025	[−.127, .001]
OS_i	→	CA_i	(ab4)	1.126	.353	.000	[.457, 1.849]*
		SMK_i	(bb1)	−.048	.286	.431	[−.597, .514]
SA_i	→	CA_i	(ab5)	.900	.122	.000	[.688, 1.160]*
		SMK_i	(bb2)	.267	.107	.005	[.058, .460]*
CA_i	→	SMK_i	(bb3)	.287	.043	.000	[.201, .370]*
OS_i	with	SA_i		.024	.006	.000	[.012, .034]*
Latent Variable^c
SES_i	→	Income_i		1.000	.000	.000	[1.000, 1.000]
		College_i		.374	.075	.000	[.233, .531]*
		Insured_i		.817	.314	.000	[.487, 1.552]*
		Employed_i		.466	.085	.000	[.303, .641]*

Variables			(path)	Est.	SD	p^a	[95% CI]^b
Within
OS_ij	→	CA_ij	(aw1)	.244	.017	.000	[.210, .277]*
		SMK_{i(j → j + 1)}	(c'w1)	.101	.029	.000	[.039, .153]*
SA_ij	→	CA_ij	(aw2)	.264	.010	.000	[.245, .283]*
		SMK_{i(j → j+1)}	(c'w2)	.087	.017	.000	[.056, .118]*
CA_ij	→	SMK_{i(j → j+1)}	(bw)	.396	.013	.000	[.372, .423]*
SMK_{i(j-1 → j)}	→	SMK_{i(j → j+1)}	(ar1)	.344	.019	.000	[.307, .375]*
		OS_ij		.032	.002	.000	[.028, .035]*
		SA_ij		.102	.005	.000	[.092, .110]*
		CA_ij		.360	.006	.000	[.350, .371]*
OS_ij	with	SA_ij		.040	.001	.000	[.038, .042]*
Between
SES_i	→	OS_i	(ab1)	−.027	.006	.000	[−.039, −.015]*
		SA_i	(ab2)	−.046	.017	.001	[−.084, −.016]*
		CA_i	(ab3)	−.085	.039	.017	[−.155, −.007]*
		SMK_i	(c'b)	−.064	.033	.025	[−.127, .001]
OS_i	→	CA_i	(ab4)	1.126	.353	.000	[.457, 1.849]*
		SMK_i	(bb1)	−.048	.286	.431	[−.597, .514]
SA_i	→	CA_i	(ab5)	.900	.122	.000	[.688, 1.160]*
		SMK_i	(bb2)	.267	.107	.005	[.058, .460]*
CA_i	→	SMK_i	(bb3)	.287	.043	.000	[.201, .370]*
OS_i	with	SA_i		.024	.006	.000	[.012, .034]*
Latent Variable^c
SES_i	→	Income_i		1.000	.000	.000	[1.000, 1.000]
		College_i		.374	.075	.000	[.233, .531]*
		Insured_i		.817	.314	.000	[.487, 1.552]*
		Employed_i		.466	.085	.000	[.303, .641]*

i indexes participants (N = 365) and j indexes EMAs (N = 31,800); Est. = undstandardized estimate (probit); SD = posterior standard deviation; p = Bayesian one-tailed p-value; a = for positive values, the one-tailed p-value is the proportion of posterior distribution above 0; b = the 2.5 and 97.5 percentiles in the asymmetric posterior distribution, credibility intervals (CI) that do not include 0 noted with an asterisk (*); c = continuous latent variable for SES (M = 0, SD = 1).

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