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Research Report: Justice made to measure: NSW legal needs survey in disadvantaged areas
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Justice made to measure: NSW legal needs survey in disadvantaged areas  ( 2006 )  Cite this report



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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)
19Car accident — property damage
39ACar accident — personal injury
39BInjury at work
39COther personal injury
Business (2)
7Problem as landlord
9Problem re own business
Consumer (5)
20FProblem re superannuation
21Problem re goods/services
22Dispute with financial institution
23Problem re insurance
56Complaint about lawyer
Credit/debt (5)
20AProblem paying bill/debt
20BDispute re credit rating
20CProblem re money owed to you
20DProblem as guarantor
20EBankruptcy
Education (6)
35AUnfair exclusion from education
35BHECS issue
35CSchool bullying/harassment
37AUnfair exclusion from education — parent
37BHECS issue — parent
37CSchool bullying/harassment — parent
Employment (5)
2ADispute re employment conditions
2BUnfair termination of employment
2CWorkplace harassment/mistreatment
2DWorkplace discrimination
2E*Other problem re employment
Government (15)
5Problem re gov. pension/benefit
31CProblem re gov. services — carer of disabled/elderly
43AProblem re gov. disability/community services
44ADispute re taxation/debt
43E*Other problem re gov. services — disabled person
44BProblem re freedom of information request
44CImmigration problem
44DLocal council problem
51Non-traffic fines you challenged
53AProblem re medical treatment — immigration detention
53BProblem re legal advice — immigration detention
53CSafety threats — immigration detention
53DHarassment/abuse by staff — immigration detention
53EProblem re release — immigration detention
57B*Problem re legal system
Civil (76)Health (11)
31BInvoluntary psychiatric hospitalisation — carer
31F*Problem re quality of medical treatment — carer
31G*Problem re disability facilities — carer
42A/52Involuntary psychiatric hospitalisation
42BOther mental health care issue
43BProblem re non-government disability services
53AProblem re medical treatment — psychiatric ward
53BProblem re legal advice — psychiatric ward
53CSafety threats — psychiatric ward
53DHarassment/abuse by staff — psychiatric ward
53EProblem re release — psychiatric ward
Housing (11)
10ABought/sold home
10BDispute with neighbour
10CHomelessness
12Tenancy problem
14Home ownership problem
16AStrata title problem
16BProblem re caravan/home estate
16CProblem re boarding house/hostel
16DProblem re retirement home/village
31ANursing home problem — carer of disabled/elderly
43CNursing home problem — disabled person
Human rightsa (8)
24ADiscrimination — marital status
24BDiscrimination — age
24CDiscrimination — gender
24DDiscrimination — religion
24EDiscrimination — sexuality
24FDiscrimination — ethnicity
24GDiscrimination — disability
31H*Discrimination — carer of disabled/eldery
Wills/estates (4)
32AMake/alter will
32BExecutor of estate
32CDispute over will/estate
32DPower of attorney
Criminal (16)Domestic violence (3)
47AVictim of domestic violence by family member
47BVictim of domestic violence by household member
48Domestic violence allegation against you
General crime (11)
46AUnfair treatment by police
46BCriminal charge
46CProblem re bail/remand
46DPolice failing to investigate crime
47CAssault victim
49Property stolen/vandalised
53AProblem re medical treatment — prison/juvenile detention
53BProblem re legal advice — prison/juvenile detention
53CSafety threats — prison/juvenile detention
53DHarassment/abuse by staff — prison/juvenile detention
53EProblem re release — prison/juvenile detention
Traffic offences (2)
50ALoss of driver’s licence
50BOther traffic fine/offence you challenged
Family (9)Family (9)
25AProblem re residence/contact for child
25BProblem re residence/contact for grandchild
27AProblem re child support payments
27BChild protection issue
27CFostering/adoption/guardianship issue
29ADivorce/separation
29BDispute re matrimonial property
31DGuardianship problem — carer of disabled/elderly
57A*Other family law problem
Unclassified (3)Unclassified (3)
31EOther problem — carer of disabled/elderly
43DOther problem re disability
57Other 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 divisionLGA
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
SydneyCampbelltown
400
402
4 992
4 779
95.7
SydneyFairfield
400
401
7 132
4 710
66
SydneySouth Sydney
400
406
10 091
6 550
64.9
HunterNewcastle
400
408
4 987
3 210
64.7
Mid-North CoastNambucca
400
414
4 977
3 012
60.5
North WesternWalgett
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 surveyMain surveyType of changeDetails of change
82S4–S6Added 3 QsTo assist screening, record gender (S4), language spoken at home (S5) and language used for interview (S6). Gender recorded at end of pilot (Q82).
11–1AMinor change to Q
22No change
33–4Minor change to Q and added 2 RCsNew RCs re benefit introduced (CDEP program; Seniors Card/Pharmaceutical Benefits Only)
513Minor change to Q and repositioningScreening Q repositioned to go immediately before the Q (14) it relates to
6–86–8No change
99Minor change to Q
1010Minor change to 1 RC
1111Change to QSimplified Q to ask only about whether pay rent. Q used as screening Q for Q12 (problems re renting)
1212Minor change to Q
13Added QAdded screening Q re whether owned property in last 12 months
1314Minor change to Q
1415No change
1516No change
16A–16BOmitted QOmitted — How long have you been at your current address (16A) or how long have you had no fixed address (16B)
17Omitted QOmitted — Did you have any problems in other places you have lived...
1817Added 1 RCNew RC re internet access — Yes, at work
1918Minor change to Q
2019No change
2120Minor change to 1 RC
2221Minor change to Q
22Added QAdded legal event — Dispute with bank/financial institution
2323No change
2424Major change to QQ re non-work related discrimination was reworded to specify legally recognised categories of discrimination (marital status, age, gender, religion, sexuality, ethnicity, disability).
27.225Repositioned QProblems with residence/contact arrangements for children — removed from Q27 and asked about in separate Q and reference to grandchildren added.
25–2626Combined 2 screening QsNo. of kids and how many live at home combined into one question.
2727Made 1 RC a separate QProblems with residence/contact arrangements for children — removed from Q27 and asked as separate Q and reference to grandchildren added.
2828Re-orderedScreening Q re marital status
response categories
28AAdded QAdded — Has marital status changed over last 12 months?
29–3229–32No change
3333Changes to RCsChanges to RCs — (1)‘Still at school’ added to ‘did not finish school’; (2) 4 RCs re certificates, diplomas, university degrees combined into 2 RCs
3434Minor change to QScreening Q re student — ‘Are you currently’ changed to ‘have you been … during the last 12 months’
3535Minor change to Q
3636No change
3737Minor change to Q
3838Omitted 1 RC1 RC (‘very well’) removed from screening Q re how well read and write English
3939No change
4040–41Minor change to Q and added 3 RCs3 RCs added re type of chronic condition or mental/physical disability (Physical disability; a learning disability; a chronic condition)
4142Change to 1 RC1 RC changed from ‘probs with care after release from hospital’ to ‘other problems with mental health care’ (made more general)
4243No change
4344Minor change to 1 RC and added 1 RCRC added—Local council problem
4445No change
4546Minor change to Q
4647Minor change to Q lead-inLead-in made more sensitive
48Added QAdded — In last 12 months, did you have allegations of domestic violence made against you, either to the police or in court?
4749No change
4850Minor change to Q
49–5051–52 No change
5153Minor change to Q
5254No change
55Added QAdded screening Q — Have you sought advice from a lawyer at any time in the last 12 months?
56Added QAdded screening Q — Did you wish to make a complaint .... because the lawyer didn’t do what you wanted.... or because you were dissatisfied...
5357No change
54–5558Major changePilot 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.
5659Minor change to Q lead-in
60Added QAdded Q to measure the month that each of the 3 most recent events occurred.
5761Minor change to Q and RCs
58–5962–63Change to Q and response formatQ 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.
6264Minor change to Q and added 2 RCs2 RCs re type of written information added (other type of written information; no written information)
6365Added 12 RCs12 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)
66Added QAdded — whether each source of assistance was useful
6467Minor change to Q
6568No change
7269Minor changes to RCsChanges 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)
7370Added 2 RCs Added 2 RCs re special services required (financial help/assistance; outreach service)
7471No change
6672Minor change to 1 RC
6773No change
68Omitted QOmitted—types of assistance people want for legal issue
69–7074Combined 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.
7175Minor change to Q
60–7576Combined 2 Qs and minor changes to RCs‘Whether matter has been resolved’ not asked separately depending on whether or not help sought.
61–7677Combined 2 Qs‘Whether satisfied with the outcome/situation’ not asked separately depending on whether or not help sought.
7778No change
7879Major change to QRather 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.
7980Minor change to Q
8081Omitted 1 RC1 RC (‘very well’) removed from Q re how well read and write English.
8182Minor change to Q
82S4Moved Q to screening section
83Added QAdded 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 categoriesTotal 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 helpw Legal event groupb
and 1200 P
2. handled alone/did nothing
Satisfaction with assistance:w Sociodemographicsa
1033 Ek
1. satisfiedw Legal event groupb
and 698 P
2. dissatisfied/neither satisfied nor dissatisfiedw Recencyc
w Resolution statusd
Resolution status:w Sociodemographicsa
2211 El
1. resolvedw Legal event groupb
and 1142 P
2. being resolved/unresolvedw Recencyc
w Action takene
Satisfaction with outcome of resolved events:w Sociodemographicsa
1357 Em
1. satisfiedw Legal event groupb
and 879 P
2. dissatisfied/neither satisfied nor dissatisfiedw 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; 06 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.



  


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Coumarelos, C, Wei , Z & Zhou, AH 2006, Justice made to measure: NSW legal needs survey in disadvantaged areas, Law and Justice Foundation of NSW, Sydney