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Appendix B: Method

Table B1: Classification of legal events

Area of law (no. of items)	Survey question no.	Legal event group (no. of items) Legal event
Civil (76)		Accident/injury (4)
	19	Car accident — property damage
	39A	Car accident — personal injury
	39B	Injury at work
	39C	Other personal injury
		Business (2)
	7	Problem as landlord
	9	Problem re own business
		Consumer (5)
	20F	Problem re superannuation
	21	Problem re goods/services
	22	Dispute with financial institution
	23	Problem re insurance
	56	Complaint about lawyer
		Credit/debt (5)
	20A	Problem paying bill/debt
	20B	Dispute re credit rating
	20C	Problem re money owed to you
	20D	Problem as guarantor
	20E	Bankruptcy
		Education (6)
	35A	Unfair exclusion from education
	35B	HECS issue
	35C	School bullying/harassment
	37A	Unfair exclusion from education — parent
	37B	HECS issue — parent
	37C	School bullying/harassment — parent
		Employment (5)
	2A	Dispute re employment conditions
	2B	Unfair termination of employment
	2C	Workplace harassment/mistreatment
	2D	Workplace discrimination
	2E*	Other problem re employment
		Government (15)
	5	Problem re gov. pension/benefit
	31C	Problem re gov. services — carer of disabled/elderly
	43A	Problem re gov. disability/community services
	44A	Dispute re taxation/debt
	43E*	Other problem re gov. services — disabled person
	44B	Problem re freedom of information request
	44C	Immigration problem
	44D	Local council problem
	51	Non-traffic fines you challenged
	53A	Problem re medical treatment — immigration detention
	53B	Problem re legal advice — immigration detention
	53C	Safety threats — immigration detention
	53D	Harassment/abuse by staff — immigration detention
	53E	Problem re release — immigration detention
	57B*	Problem re legal system
Civil (76)		Health (11)
	31B	Involuntary psychiatric hospitalisation — carer
	31F*	Problem re quality of medical treatment — carer
	31G*	Problem re disability facilities — carer
	42A/52	Involuntary psychiatric hospitalisation
	42B	Other mental health care issue
	43B	Problem re non-government disability services
	53A	Problem re medical treatment — psychiatric ward
	53B	Problem re legal advice — psychiatric ward
	53C	Safety threats — psychiatric ward
	53D	Harassment/abuse by staff — psychiatric ward
	53E	Problem re release — psychiatric ward
		Housing (11)
	10A	Bought/sold home
	10B	Dispute with neighbour
	10C	Homelessness
	12	Tenancy problem
	14	Home ownership problem
	16A	Strata title problem
	16B	Problem re caravan/home estate
	16C	Problem re boarding house/hostel
	16D	Problem re retirement home/village
	31A	Nursing home problem — carer of disabled/elderly
	43C	Nursing home problem — disabled person
		Human rightsa (8)
	24A	Discrimination — marital status
	24B	Discrimination — age
	24C	Discrimination — gender
	24D	Discrimination — religion
	24E	Discrimination — sexuality
	24F	Discrimination — ethnicity
	24G	Discrimination — disability
	31H*	Discrimination — carer of disabled/eldery
		Wills/estates (4)
	32A	Make/alter will
	32B	Executor of estate
	32C	Dispute over will/estate
	32D	Power of attorney
Criminal (16)		Domestic violence (3)
	47A	Victim of domestic violence by family member
	47B	Victim of domestic violence by household member
	48	Domestic violence allegation against you
		General crime (11)
	46A	Unfair treatment by police
	46B	Criminal charge
	46C	Problem re bail/remand
	46D	Police failing to investigate crime
	47C	Assault victim
	49	Property stolen/vandalised
	53A	Problem re medical treatment — prison/juvenile detention
	53B	Problem re legal advice — prison/juvenile detention
	53C	Safety threats — prison/juvenile detention
	53D	Harassment/abuse by staff — prison/juvenile detention
	53E	Problem re release — prison/juvenile detention
		Traffic offences (2)
	50A	Loss of driver’s licence
	50B	Other traffic fine/offence you challenged
Family (9)		Family (9)
	25A	Problem re residence/contact for child
	25B	Problem re residence/contact for grandchild
	27A	Problem re child support payments
	27B	Child protection issue
	27C	Fostering/adoption/guardianship issue
	29A	Divorce/separation
	29B	Dispute re matrimonial property
	31D	Guardianship problem — carer of disabled/elderly
	57A*	Other family law problem
Unclassified (3)		Unclassified (3)
	31E	Other problem — carer of disabled/elderly
	43D	Other problem re disability
	57	Other problem

a Human rights events are not related to employment.
* Legal events marked with an asterisk were not specifically asked about in the survey, but were identified by post-coding. While the question number listed for each of these events in the table does not appear on the survey, it indicates the survey question from which the event was post-coded. For example, the legal event numbered 43E was post-coded from question 43.

Table B2a: Gender and age breakdown in sample and population, Campbelltown, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	64	21	33	37	19	14	188
	(%)	(16)	(5.2)	(8.2)	(9.2)	(4.7)	(3.5)	(46.9)
Females	no.	24	57	49	44	20	19	213
	(%)	(6)	(14.2)	(12.2)	(11)	(5)	(4.7)	(53.1)
Males and females	no.	88	78	82	81	39	33	401
	(%)	(21.9)	(19.5)	(20.4)	(20.2)	(9.7)	(8.2)	(100)
Population
Males	no.	13 091	10 302	10 790	10 594	6 554	4 404	55 735
	(%)	(11.5)	(9.1)	(9.5)	(9.3)	(5.8)	(3.9)	(49.1)
Females	no.	12 299	10 888	11 776	10 957	6 115	5 689	57 724
	(%)	(10.8)	(9.6)	(10.4)	(9.7)	(5.4)	(5)	(50.9)
Males and females	no.	25 390	21 190	22 566	21 551	12 669	10 093	113 459
	(%)	(22.4)	(18.7)	(19.9)	(19)	(11.2)	(8.9)	(100)

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (405) or the total estimated population in the LGA (55 840), as appropriate. (Data on age were missing for one survey participant.)
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 8.6% x 405 = 35).
a. one-way x2 for gender: x2=0.00, df=1, p=0.957 (N=406)
b. one-way x2 for age: x2=3.52, df=5, p=0.621 (N=405)
c. two-way x2 for gender by age: x2=19.27, df=5, p=0.002 (N=405)

Table B2b: Gender and age breakdown in sample and population, Fairfield, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	45	35	38	26	23	26	193
	(%)	(11.3)	(8.8)	(9.5)	(6.5)	(5.8)	(6.5)	(48.3)
Females	no.	38	40	49	45	20	15	207
	(%)	(9.5)	(10)	(12.3)	(11.3)	(5)	(3.8)	(51.8)
Males and females	no.	83	75	87	71	43	41	400
	(%)	(20.8)	(18.8)	(21.8)	(17.8)	(10.8)	(10.3)	(100)
Population
Males	no.	14 539	13 620	14 756	12 999	8 866	8 830	73 610
	(%)	(9.8)	(9.2)	(10)	(8.8)	(6)	(6)	(49.7)
Females	no.	14 281	13 959	14 237	13 014	8 280	10 579	74 350
	(%)	(9.7)	(9.4)	(9.6)	(8.8)	(5.6)	(7.1)	(50.3)
Males and females	no.	28 820	27 579	28 993	26 013	17 146	19 409	147 960
	(%)	(19.5)	(18.6)	(19.6)	(17.6)	(11.6)	(13.1)	(100)

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (400) or the total estimated population in the LGA (147 960), as appropriate. (Data on age were missing for one survey participant.)
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 9.8% x 400 = 39).
a. one-way x2 for gender: x2=0.42, df=1, p=0.516 (N=401)
b. one-way x2 for age: x2=4.04, df=5, p=0.544 (N=400)
c. two-way x2 for gender by age: x2=16.09, df=5, p=0.007 (N=400)

Table B2c: Gender and age breakdown in sample and population, South Sydney, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	41	68	45	28	15	24	221
	(%)	(10.1)	(16.8)	(11.1)	(6.9)	(3.7)	(5.9)	(54.6)
Females	no.	22	59	42	27	22	12	184
	(%)	(5.4)	(14.6)	(10.4)	(6.7)	(5.4)	(3)	(45.4)
Males and females	no.	63	127	87	55	37	36	405
	(%)	(15.6)	(31.4)	(21.5)	(13.6)	(9.1)	(8.9)	(100)
Population
Males	no.	4 794	9 658	6 410	3 838	2 727	2 895	30 322
	(%)	(8.6)	(17.3)	(11.5)	(6.9)	(4.9)	(5.2)	(54.3)
Females	no.	4 762	8 002	4 234	3 172	2 233	3 115	25 518
	(%)	(8.5)	(14.3)	(7.6)	(5.7)	(4)	(5.6)	(45.7)
Males and females	no.	9 556	17 660	10 644	7 010	4 960	6 010	55 840
	(%)	(17.1)	(31.6)	(19.1)	(12.6)	(8.9)	(10.8)	(100)

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (405) or the total estimated population in the LGA (55 840), as appropriate. (Data on age were missing for one survey participant.)
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 8.6% x 405 = 35).
a. one-way x2 for gender: x2=0.00, df=1, p=0.957 (N=406)
b. one-way x2 for age: x2=3.52, df=5, p=0.621 (N=405)
c. two-way x2 for gender by age: x2=19.27, df=5, p=0.002 (N=405)

Table B2d: Gender and age breakdown in sample and population, Newcastle, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	43	35	35	36	19	29	197
	(%)	(10.5)	(8.6)	(8.6)	(8.8)	(4.7)	(7.1)	(48.3)
Females	no.	32	38	42	39	29	31	211
	(%)	(7.8)	(9.3)	(10.3)	(9.6)	(7.1)	(7.6)	(51.7)
Males and females	no.	75	73	77	75	48	60	408
	(%)	(18.4)	(17.9)	(18.9)	(18.4)	(11.8)	(14.7)	(100)
Population
Males	no.	11 036	11 097	10 229	9 160	6 890	9 617	58 029
	(%)	(9.2)	(9.3)	(8.6)	(7.7)	(5.8)	(8)	(48.6)
Females	no.	11 235	10 777	10 110	9 037	6 759	13 534	61 452
	(%)	(9.4)	(9)	(8.5)	(7.6)	(5.7)	(11.3)	(51.4)
Males and females	no.	22 271	21 874	20 339	18 197	13 649	23 151	119 481
	(%)	(18.6)	(18.3)	(17)	(15.2)	(11.4)	(19.4)	(100)

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (408) or the total estimated population in the LGA (119 481), as appropriate.
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 9.2% x 408 = 38).
a. one-way x2 for gender: x2=0.01, df=1, p=0.909 (N=408)
b. one-way x2 for age: x2=8.17, df=5, p=0.147 (N=408)
c. two-way x2 for gender by age: x2=14.39, df=5, p=0.013 (N=408)

Table B2e: Gender and age breakdown in sample and population, Nambucca, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	32	24	30	33	26	57	202
	(%)	(7.7)	(5.8)	(7.2)	(8)	(6.3)	(13.8)	(48.8)
Females	no.	16	17	40	55	38	46	212
	(%)	(3.9)	(4.1)	(9.7)	(13.3)	(90.2)	11.1	-51.2
Males and females	no.	48	41	70	88	64	103	414
	(%)	-11.6	-9.9	-16.9	-21.3	-15.5	-24.9	-100
Population
Males	no.	981	734	1 100	1 367	1 130	1 833	7 145
	(%)	-6.8	-5.1	-7.6	-9.4	-7.8	-12.6	-49.2
Females	no.	873	786	1 263	1 310	1 128	2 024	7 384
	(%)	-6	-5.4	-8.7	-9	-7.8	-13.9	-50.8
Males and females	no.	1 854	1 520	2 363	2 677	2 258	3 857	14 529
	(%)	-12.8	-10.5	-16.3	-18.4	-15.5	-26.5	-100

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (414) or the total estimated population in the LGA (14 529), as appropriate.
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 6.8% x 414 = 28).
a. one-way x2 for gender: x2=0.03, df=1, p=0.875 (N=414)
b. one-way x2 for age: x2=2.91, df=5, p=0.714 (N=414)
c. two-way x2 for gender by age: x2=20.35, df=5, p=0.001 (N=414)

Table B2f: Gender and age breakdown in sample and population, Walgett, 2003

Age (years)		15–24	25–34	35–44	45–54	55–64	65+	15–65+
Sample
Males	no.	33	31	42	43	38	37	224
	(%)	(8.3)	(7.8)	(10.5)	(10.8)	(9.5)	(9.3)	(56)
Females	no.	13	38	36	37	30	22	176
	(%)	(3.3)	(9.5)	(9)	(9.3)	(7.5)	(5.5)	(44)
Males and females	no.	46	69	78	80	68	59	400
	(%)	(11.5)	(17.3)	(19.5)	(20)	(17)	(14.8)	(100)
Population
Males	no.	494	606	676	716	640	549	3681
	(%)	(7.6)	(9.4)	(10.4)	(11.1)	(9.9)	(8.5)	(56.8)
Females	no.	414	530	553	511	420	368	2796
	(%)	(6.4)	(8.2)	(8.5)	(7.9)	(6.5)	(5.7)	(43.2)
Males and females	no	908	1136	1229	1227	1060	917	6477
	(%)	(14)	(17.5)	(19)	(18.9)	(16.4)	(14.2)	(100)

Notes:
1. Population data are estimated resident population as at 30 June 2003 (unpublished ABS data).
2. Each % is based on the cell no. divided by the total sample no. in the LGA (400) or the total estimated population in the LGA (6477), as appropriate.
3. Three chi-square tests were conducted comparing sample numbers with the corresponding expected numbers based on the population data. (The expected number for each cell = cell % for the population multiplied by the total sample no., e.g. expected no. of males 15–24 years = 7.6% x 400 = 30).
a. one-way x2 for gender: x2=0.11, df=1, p=0.737 (N=400)
b. one-way x2 for age: x2=2.32, df=5, p=0.803 (N=400)
c. two-way x2 for gender by age: x2=10.41, df=5, p=0.065 (N=400)

Table B3: Number of target interviews, completed interviews, phone numbers in pool and phone numbers called, 2003

Statistical division	LGA	Target no. of interviews	No. of completed interviews	No. of phone numbers in pool	No. of phone numbers called from pool	% of phone numbers called from pool
Sydney	Campbelltown	400	402	4 992	4 779	95.7
Sydney	Fairfield	400	401	7 132	4 710	66
Sydney	South Sydney	400	406	10 091	6 550	64.9
Hunter	Newcastle	400	408	4 987	3 210	64.7
Mid-North Coast	Nambucca	400	414	4 977	3 012	60.5
North Western	Walgett	400	400	2 464	2 464	100
Total		2 400	2 431	34 643	24 725	71.4

Table B4a: Outcome of attempted phone contact, Campbelltown, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	402
Refuseda	-	1454	Outright refusal (1355)
			Refused monitoring by a survey supervisor (78)
			Refused to complete interview (21)
Not eligible	NE	520	Failed to meet survey coverage criteria (419)
			Business number (68)
			Language barrierb (33)
Not contacted and eligible	NC	202	Unable to determine appointment at call back
Not interviewed	NI	574	Contacted but surplus to quota needs
Not applicable	-	1627	Phone number no longer exists (848)
			No contact after 5 attemptsc (779)
Numbers called from pool		4779
Numbers not called from pool		213
Total numbers in pool		4992

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B4b: Outcome of attempted phone contact, Fairfield, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	401
Refuseda	-	1465	Outright refusal (1374)
			Refused monitoring by a survey supervisor (18)
			Refused to complete interview (73)
Not eligible	NE	1097	Failed to meet survey coverage criteria (835)
			Business number (41)
			Language barrierb (221)
Not contacted and eligible	NC	79	Unable to determine appointment at call back
Not interviewed	NI	278	Contacted but surplus to quota needs
Not applicable	-	1390	Phone number no longer exists (904)
			No contact after 5 attemptsc (486)
Numbers called from pool		4710
Numbers not called from pool		2422
Total numbers in pool		7132

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B4c: Outcome of attempted phone contact, South Sydney, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	406
Refuseda	-	1 800	Outright refusal (1718)
			Refused monitoring by a survey supervisor (18)
			Refused to complete interview (64)
Not eligible	NE	749	Failed to meet survey coverage criteria (540)
			Business number (131)
			Language barrierb (78)
Not contacted and eligible	NC	201	Unable to determine appointment at call back
Not interviewed	NI	468	Contacted but surplus to quota needs
Not applicable	-	2 926	Phone number no longer exists (1498)
			No contact after 5 attemptsc (1428)
Numbers called from pool		6 550
Numbers not called from pool		3 541
Total numbers in pool		10 091

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B4d: Outcome of attempted phone contact, Newcastle, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	408
Refuseda	-	1057	Outright refusal (1036)
			Refused monitoring by a survey supervisor (6)
			Refused to complete interview (15)
Not eligible	NE	350	Failed to meet survey coverage criteria (292)
			Business number (43)
			Language barrierb (15)
Not contacted and eligible	NC	174	Unable to determine appointment at call back
Not interviewed	NI	242	Contacted but surplus to quota needs
Not applicable	-	979	Phone number no longer exists (395)
			No contact after 5 attemptsc (584)
Numbers called from pool		3210
Numbers not called from pool		1777
Total numbers in pool		4987

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B4e: Outcome of attempted phone contact, Nambucca, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	414
Refuseda	-	949	Outright refusal (922)
			Refused monitoring by a survey supervisor (9)
			Refused to complete interview (18)
Not eligible	NE	341	Failed to meet survey coverage criteria (308)
			Business number (27)
			Language barrierb (6)
Not contacted and eligible	NC	127	Unable to determine appointment at call back
Not interviewed	NI	355	Contacted but surplus to quota needs
Not applicable	-	826	Phone number no longer exists (320)
			No contact after 5 attemptsc (506)
Numbers called from pool		3012
Numbers not called from pool		1965
Total numbers in pool		4977

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B4f: Outcome of attempted phone contact, Walgett, 2003

Outcome	Groves’s typology	No.	Examples of outcome
Interview completed	I	400
Refuseda	-	744	Outright refusal (692)
			Refused monitoring by a survey supervisor (30)
			Refused to complete interview (22)
Not eligible	NE	193	Failed to meet survey coverage criteria (133)
			Business number (51)
			Language barrierb (9)
Not contacted and eligible	NC	64	Unable to determine appointment at call back
Not interviewed	NI	296	Contacted but surplus to quota needs
Not applicable	-	767	Phone number no longer exists (418)
			No contact after 5 attemptsc (349)
Numbers called from pool		2464
Numbers not called from pool		0
Total numbers in pool		2464

a R, the number of refusals who were eligible to participate, was unknown. There was no information on eligibility to participate for the outright refusals and those who refused monitoring by a survey supervisor.
b Interviewer could not determine the language used by respondent.
c On each attempt, either there was no answer after 10 rings, the phone was engaged, the call was answered by an answering machine or the number was dead.

Table B5: Cooperation and response rate for each LGA, 2003

LGA	Estimated no. of eligible refusals			Cooperation Rate I/(I+R)			Response Rate I/(I+R+NC+NI)
	R1	R2	R3	Min.	Max.	Best estimate	Min.	Max.	Best estimate
Campbelltown	1454	21	1009	0.22	0.95	0.28	0.15	0.34	0.18
Fairfield	1465	73	599	0.21	0.85	0.4	0.18	0.48	0.3
South Sydney	1800	64	1061	0.18	0.86	0.28	0.14	0.36	0.19
Newcastle	1057	15	742	0.28	0.96	0.35	0.22	0.49	0.26
Nambucca	949	18	687	0.3	0.96	0.38	0.22	0.45	0.26
Walgett	744	22	593	0.35	0.95	0.4	0.27	0.51	0.3
Total	7469	213	4691	0.25	0.92	0.34	0.19	0.43	0.24

Notes:
R1 = total no. of refusals. Used to calculate minimum cooperation and response rates.
R2 = no. of partial interviews. Used to calculate maximum cooperation and response rates.
R3 = R1 multiplied by estimated proportion of eligible persons among those who refused
= R1 x ((I+NC+NI)/(I+NE+NC+NI)). Used to calculate the best estimate of cooperation and response rates.
(N.B. Values of I, NC, NI and NE are provided in tables B4a to B4f.)

Table B6: Differences between pilot and main surveys

Item no.
Pilot survey	Main survey	Type of change	Details of change
82	S4–S6	Added 3 Qs	To assist screening, record gender (S4), language spoken at home (S5) and language used for interview (S6). Gender recorded at end of pilot (Q82).
1	1–1A	Minor change to Q
2	2	No change
3	3–4	Minor change to Q and added 2 RCs	New RCs re benefit introduced (CDEP program; Seniors Card/Pharmaceutical Benefits Only)
5	13	Minor change to Q and repositioning	Screening Q repositioned to go immediately before the Q (14) it relates to
6–8	6–8	No change
9	9	Minor change to Q
10	10	Minor change to 1 RC
11	11	Change to Q	Simplified Q to ask only about whether pay rent. Q used as screening Q for Q12 (problems re renting)
12	12	Minor change to Q
	13	Added Q	Added screening Q re whether owned property in last 12 months
13	14	Minor change to Q
14	15	No change
15	16	No change
16A–16B		Omitted Q	Omitted — How long have you been at your current address (16A) or how long have you had no fixed address (16B)
17		Omitted Q	Omitted — Did you have any problems in other places you have lived...
18	17	Added 1 RC	New RC re internet access — Yes, at work
19	18	Minor change to Q
20	19	No change
21	20	Minor change to 1 RC
22	21	Minor change to Q
	22	Added Q	Added legal event — Dispute with bank/financial institution
23	23	No change
24	24	Major change to Q	Q re non-work related discrimination was reworded to specify legally recognised categories of discrimination (marital status, age, gender, religion, sexuality, ethnicity, disability).
27.2	25	Repositioned Q	Problems with residence/contact arrangements for children — removed from Q27 and asked about in separate Q and reference to grandchildren added.
25–26	26	Combined 2 screening Qs	No. of kids and how many live at home combined into one question.
27	27	Made 1 RC a separate Q	Problems with residence/contact arrangements for children — removed from Q27 and asked as separate Q and reference to grandchildren added.
28	28	Re-ordered	Screening Q re marital status
		response categories
	28A	Added Q	Added — Has marital status changed over last 12 months?
29–32	29–32	No change
33	33	Changes to RCs	Changes to RCs — (1)‘Still at school’ added to ‘did not finish school’; (2) 4 RCs re certificates, diplomas, university degrees combined into 2 RCs
34	34	Minor change to Q	Screening Q re student — ‘Are you currently’ changed to ‘have you been … during the last 12 months’
35	35	Minor change to Q
36	36	No change
37	37	Minor change to Q
38	38	Omitted 1 RC	1 RC (‘very well’) removed from screening Q re how well read and write English
39	39	No change
40	40–41	Minor change to Q and added 3 RCs	3 RCs added re type of chronic condition or mental/physical disability (Physical disability; a learning disability; a chronic condition)
41	42	Change to 1 RC	1 RC changed from ‘probs with care after release from hospital’ to ‘other problems with mental health care’ (made more general)
42	43	No change
43	44	Minor change to 1 RC and added 1 RC	RC added—Local council problem
44	45	No change
45	46	Minor change to Q
46	47	Minor change to Q lead-in	Lead-in made more sensitive
	48	Added Q	Added — In last 12 months, did you have allegations of domestic violence made against you, either to the police or in court?
47	49	No change
48	50	Minor change to Q
49–50	51–52	No change
51	53	Minor change to Q
52	54	No change
	55	Added Q	Added screening Q — Have you sought advice from a lawyer at any time in the last 12 months?
	56	Added Q	Added screening Q — Did you wish to make a complaint .... because the lawyer didn’t do what you wanted.... or because you were dissatisfied...
53	57	No change
54–55	58	Major change	Pilot asked participants to identify ‘most significant’ legal event in the last 12 months and the 2 most recent events in the last 12 months. Main survey only asked participants to identify the 3 most recent events.
56	59	Minor change to Q lead-in
	60	Added Q	Added Q to measure the month that each of the 3 most recent events occurred.
57	61	Minor change to Q and RCs
58–59	62–63	Change to Q and response format	Q changed to ask first about ‘most important reason’ why didn’t seek help and then follow with ‘other reasons’ why didn’t seek help. Pre-coded RCs removed and replaced with open-response format.
62	64	Minor change to Q and added 2 RCs	2 RCs re type of written information added (other type of written information; no written information)
63	65	Added 12 RCs	12 new sources of assistance added (published self-help source; internet site(s); local council; library; employer; school/school counsellor/teacher; other professional; insurance company/broker; private agency/organisation; company/business; LawAccess; Aboriginal legal services)
	66	Added Q	Added — whether each source of assistance was useful
64	67	Minor change to Q
65	68	No change
72	69	Minor changes to RCs	Changes to RCs re problems in trying to get help—1 RC (communication problems) broken down into 2 RCs (language problems; difficulty understanding advice/information given); and 1 new RC (delay in getting a response)
73	70	Added 2 RCs	Added 2 RCs re special services required (financial help/assistance; outreach service)
74	71	No change
66	72	Minor change to 1 RC
67	73	No change
68		Omitted Q	Omitted—types of assistance people want for legal issue
69–70	74	Combined 2 Qs and change to response format	‘Kind of help’ and ‘how was it given’ combined into 1 Q. Pre-coded RCs removed and replaced with open-response format.
71	75	Minor change to Q
60–75	76	Combined 2 Qs and minor changes to RCs	‘Whether matter has been resolved’ not asked separately depending on whether or not help sought.
61–76	77	Combined 2 Qs	‘Whether satisfied with the outcome/situation’ not asked separately depending on whether or not help sought.
77	78	No change
78	79	Major change to Q	Rather than ask about ethnic background (and include Aboriginal/Torres Strait Islander as one RC), Q changed to only ask about whether an Aboriginal/Torres Strait Islander. Ethnic background gauged from previous Q (unchanged) on country of birth.
79	80	Minor change to Q
80	81	Omitted 1 RC	1 RC (‘very well’) removed from Q re how well read and write English.
81	82	Minor change to Q
82	S4	Moved Q to screening section
	83	Added Q	Added to record language in which interview conducted.

Note: Q refers to question and RC refers to response category.

Table B7: Predictor and outcome variables in each regression model

Binary outcome variable and its categories	Potential predictors and their categories	Total no. of participants (P) and events (E) in model
STANDARD BINARY LOGISTIC REGRESSION MODELS
Reporting legal events of any type:	w Sociodemographicsa	1988 Pg
1. 1+ event of any type
2. no event
Reporting accident/injury events:	w Sociodemographicsa	1988 Pg
1. 1+ accident/injury event
2. no accident/injury event
Reporting credit/debt events:	w Sociodemographicsa	1988 Pg
1. 1+ credit/debt event
2. no credit/debt event
Reporting consumer events:	w Sociodemographicsa	1988 Pg
1. 1+ consumer event
2. no consumer event
Reporting education events:	w Sociodemographicsa	913 Ph
1. 1+ education event
2. no education event
Reporting employment events:	w Sociodemographicsa	1195 Pi
1. 1+ employment event
2. no employment event
Reporting government events:	w Sociodemographicsa	1988 Pg
1. 1+ government event
2. no government event
Reporting housing events:	w Sociodemographicsa	1988 Pg
1. 1+ housing event
2. no housing event
Reporting wills/estates events:	w Sociodemographicsa	1988 Pg
1. 1+ wills/estates event
2. no wills/estates event
Reporting general crime events:	w Sociodemographicsa	1988 Pg
1. 1+ general crime event
2. no general crime event
Reporting family events:	w Sociodemographicsa	1988 Pg
1. 1+ family event
2. no family event
MIXED-EFFECTS BINARY LOGISTIC REGRESSION MODELS
Action taken:	w Sociodemographicsa	2380 Ej
1. sought help	w Legal event groupb	and 1200 P
2. handled alone/did nothing
Satisfaction with assistance:	w Sociodemographicsa	1033 Ek
1. satisfied	w Legal event groupb	and 698 P
2. dissatisfied/neither satisfied nor dissatisfied	w Recencyc
	w Resolution statusd
Resolution status:	w Sociodemographicsa	2211 El
1. resolved	w Legal event groupb	and 1142 P
2. being resolved/unresolved	w Recencyc
	w Action takene
Satisfaction with outcome of resolved events:	w Sociodemographicsa	1357 Em
1. satisfied	w Legal event groupb	and 879 P
2. dissatisfied/neither satisfied nor dissatisfied	w Recencyc
	w Action takene
	w Method of resolutionf

a The term ‘sociodemographics’ refers to the following potential predictor variables, with the following categories: gender (female, male); age in years (15–24, 25–34, 35–44, 45–54, 55–64, 65+); Indigenous status (Indigenous, non-Indigenous), country of birth (English speaking, non-English speaking); disability status (disability, no disability), personal income in $/week (0–200, 200–499, 500–999, 1000+); and education level (didn’t finish/at school, Year 10/equivalent, Year 12/equivalent, certificate/diploma, university degree).
b Legal event group had 15 categories, including 11 civil law categories (accident/injury, business, consumer, credit/debt, education, employment, government, health, housing, human rights, wills/estates), three criminal law categories (domestic violence, general crime, traffic offences), and one family law category. The reference category is the average of all 15 legal event groups.
c Recency of the event had two categories: 7–12 months ago; 0–6 months ago.
d Resolution status of the event had three categories (when used as a predictor variable): resolved; being resolved; unresolved.
e Action taken in response to event had three categories: sought help; handled alone; did nothing.
f Method of resolution had three categories: on own; through legal proceedings; some other way.
g Data were missing on one or more sociodemographic factors for 443 participants.
h This regression is based on the 1076 participants who had the potential to experience an education event, that is, on participants who were full- or part-time students, or were responsible for a student. Of these, 163 had missing data on one or more sociodemographic factors and were excluded from the regression.
i This regression is based on the 1417 participants who had the potential to experience an employment event, that is, on participants who were employed full- or part-time at some time during the reference period. Of these, 222 had missing data on one or more sociodemographic factors and were excluded from the regression.
j Information on action taken was provided for 2921 events. Of these, 541 events had missing data on one or more of the predictor variables and were excluded from the regression.
k Information on satisfaction with the assistance received for legal events was provided for 1307 events. Of these, 274 events had missing data on one or more of the predictor variables and were excluded from the regression.
l Information on the resolution status of legal events was provided for 2873 events. Of these, 662 events had missing data on one or more of the predictor variables and were excluded from the regression.
m Information on satisfaction with the outcome of resolved legal events was provided for 1735 events. Of these, 378 events had missing data on one or more of the predictor variables and were excluded from the regression.
Note: The reference category for each potential predictor is presented in italics above.

Mixed-effects logistic regression

The mixed-effects logistic regression models were run using the package MIXNO (Hedeker 1999, 2002). MIXNO can be used to analyse binary outcome variables where the data are correlated as a result of clustered designs. In the present study, the last four outcome variables involved clustered data with some participants having more than one legal event. The mixed-effects model allows for the possibility that the present data (for events) within clusters (participants) are dependent. For example, it allows for the possibility that experiencing a particular type of legal event increases the probability of experiencing another similar or related legal event. The model treats participants as a random effect, estimates the degree of dependence within participants, and adjusts for the level of dependence resulting from the clustered data. Adjusting for any dependence means that the model avoids falsely rejecting the null hypothesis too often, that is, it avoids falsely concluding that predictors are significant when they are not (Gibbons & Hedeker 1997). For further information on the mixed-effects logistic regression technique, see Hedeker (1999, 2002).

Variable selection in standard and mixed-effects regressions

A ‘full model’ approach was used for all the logistic regressions conducted, both standard and mixed-effects. That is, all the potential predictor variables were retained in each final model, regardless of whether they were statistically significant (at the 0.05 level). This approach allowed the effects of all the independent variables on the outcome variable to be considered together. It also allowed comparison of the same set of independent variables (the sociodemographic variables) across the 11 outcome variables involving reporting legal events (i.e. reporting any event; reporting each of 10 types of events). Interaction terms were not included in the models.
Significance of predictors in standard and mixed-effects regressions

The standard binary logistic regressions were conducted with SPSS which outputs the Wald statistic and accompanying probability (p) value for each overall predictor and for each comparison. The summary tables for the standard regression models present these statistics.

MIXNO computes Z and p statistics for each comparison examined, but does not present statistics on the significance of each predictor overall (except where the predictor has two categories, and therefore only one comparison). In addition to the MIXNO output, likelihood ratio test statistics (chi-square (2) and p) were computed for all predictors with three or more categories. The tables in Appendix C that provide the full results of the mixed-effects regression models present the Z statistics for all comparisons (and for binary predictors), and the 2 statistics for the overall significance of predictors with three or more categories.