|
Items in cart [0] |
Questions? Call 888-624-8373 |
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 169
B
The Methodology olL
Countint the Homeless
Charles D. Cowan, William R. Breakey,
and Pamela,l. Fischer
Although there has been great interest in the number of homeless
Americans in the past decade, few rigorously designed censuses of
homeless populations have been mounted. When counts have been
attempted, they have been local in scope, and problems with the
enumeration methods have not been widely discussed.
The impetus for determining the number of homeless people results
largely from increased interest in the projection of service needs and the
distribution of resources for the homeless. For example, the U. S.
Department of Housing and Urban Development has conducted its own
research on the need for emergency shelters; the National Institute for
Mental Health administers a number of service programs and has funded
several research studies on the demand for services by the homeless;
and P.L.'s 98-151 and 98-181 charged the Emergency Food and Shelter
National Board with the quick distribution of $40 million to supplement
and extend emergency food and shelter services nationwide. In this last
case, the distribution of the funds was determined by considering both
the overall unemployment rate for an area and the total number of
unemployed people within a civil jurisdiction. Although the Emergency
Food and Shelter National Board recognizes that "unemployment rates
and numbers are not a totally valid surrogate for need or poverty" (1983),
Charles D. Cowan is chief statistician, Center for Education Statistics, U.S. Department
of Education. William R. Breakey is director of the Community Psychiatry Program,
Department of Psychiatry and Behavioral Sciences, The Johns Hopkins Medical Institutions.
Pamela J. Fischer is assistant professor, Department of Psychiatry and Behavioral Sciences,
The Johns Hopkins Medical Institutions.
169
OCR for page 170
170 APPENDIX B
they could find no other data "which were current, uniform and available
within the time frame."
Counting the homeless population is extremely difficult because of the
lack of a clear definition of homelessness, the mobility of the population,
and the cyclical nature of homelessness for many individuals. In addition,
homeless people are often reluctant to be interviewed, and many of them
remain invisible even to the most diligent of researchers. There is no
uniform method for counting the homeless, and very few good studies
have been done. Three approaches have been used: indirect estimation,
single-contact censuses, and capture-recapture studies. Each method,
while offering some benefits, suffers from certain technical inadequacies.
INDIRECT ESTIMATION
The indirect method involves eliciting information from knowledgeable
sources, or key informants, about the number of homeless people in an
area or the number receiving services, including tallies of the number of
people using shelters and other services and estimates of the number of
people turned away or otherwise not receiving services. This type of
study requires that each of the informants must define "homeless"
according to standard criteria and report the number of homeless people
encountered over the same period and that the service agencies must be
exhaustively surveyed. Because different agencies or groups provide
services for the same set of people, some allowance has to be made for
double (or multiple) counting of individuals. Unduplication is extremely
difficult and requires detailed knowledge of the area and the services
under study.
The great advantage of indirect estimation is that it is the most
economical method. Data collection in this type of study can be done by
telephone or by letter with staff in service agencies and local government
bureaus. In addition, publications and service reports that can be used
as a base for the counts are often available from the agencies and bureaus.
The major disadvantage of this method is its tendency to produce inflated
estimates due to duplication. The necessity of reliance on the advice of
key informants whose perceptions of the size and nature of the homeless
population are biased by their own particular set of experiences and who
may be unaware of the extent of the overlap in service utilization may
also badly skew that population estimate.
Two much-quoted national studies have reported widely divergent
estimates of the national homeless population as determined by indirect
estimation techniques. Hobbs and Snyder (1982) reported that "in 1980
. . . we concluded that approximately 1 percent of the population, or 2.2
million people, lacked shelter. We arrived at that conclusion on the basis
OCR for page 171
APPENDIX B 171
of information received from more than 100 agencies and organizations
in 25 cities and states.... It is as accurate an estimate as anyone in the
country could offer, yet it lacks absolute statistical certainty." This
number, despite the flaws inherent in trying to obtain a national estimate
from such a small and disparate sample, was for some time the only
number available nationally and so attained a certain level of currency.
The second national study, conducted by the U.S. Department of
Housing and Urban Development (HUD) (Bobo, 1984), also used the
indirect method. Five hundred knowledgeable observers were contacted
to obtain local estimates of the number of homeless people in a sample
of 60 urban areas. In addition, HUD researchers spoke with 184 shelter
managers in a separate random sample of shelters, visited 10 metropolitan
areas, and interviewed officials in all 50 states. The HUD report estimated
that there were from 250,000 to 300,000 homeless people in the United
States.
There were several major flaws in the design and conduct of the HUD
research. The first problem was that the contacts made in each of the 60
metropolitan areas were done by "snowball sampling," in which the
interviewers first contacted sample units (shelters) that were known to
them, and then used the information provided by shelter operators and
other knowledgeable people to get names of other shelters or locations
not on the initial list. Repetition of this technique should eventually lead
to a complete list of all shelters, but several interactions are needed to
be certain that the list is complete. Furthermore, this method leads to a
different probability of contact for each unit in the population, since the
probability is a function of how frequently the shelter is mentioned.
Another problem is the lack of uniformity of response or coverage
from the 60 metropolitan areas included in the survey. Many advocates
and others deal only with homeless people in their own immediate area,
and may have no direct experience with homeless people in other parts
of the metropolitan area or a good measure of how much movement there
is between areas within the city. Obtaining estimates from people who
have studied the homeless population for a whole city may be no better,
since their methodologies and definitions vary. The city of Baltimore
provides an example, where estimates of the number of homeless people
there have ranged from 2,000 to 15,000 (Baltimore City Council, 1983;
Health and Welfare Council of Central Maryland, 1983, 19861. Other
cities have similar ranges, depending on how the research was done.
Aggregating these numbers for 60 metropolitan areas and then weighting
the numbers up to the national level may only be expected to produce
estimates with larger meaningless ranges.
Applebaum (1986) points out that another problem with the HUD study
is that it used population data for Rand McNally metropolitan areas
OCR for page 172
172 APPENDIX B
(RMAs), which include but are much larger than the cities named in the
survey. HUD asked respondents about the numbers of homeless estimated
for the cities, but applied the reported homeless counts to the whole
RMAs. This would lead to an underestimate of the number of homeless
in the entire RMA; summing these estimates and weighting them up by
the ratio of the U.S. population to the population of the sample RMAs
would lead to an underestimate of the size of the homeless population
for the entire country.
Finally, many local studies, including some of those incorporated into
the HUD (Bobo, 1984) and Hombs and Snyder (1982) estimates, fail to
distinguish between "point" estimates, which deal with the number of
homeless on a particular day, and "period" estimates, which attempt to
give a measure of the numbers of homeless over a period such as a year.
The problems in deriving accurate period estimates are much more
complex than those in deriving point estimates; estimates of the two
types should never be combined.
A good example of an indirect count conducted at the state level is
that by the Health and Welfare Council of Central Maryland (19861. A
list was developed of all shelter providers in the state, and data were
collected from each one regarding the numbers of people sheltered on
specific nights throughout the year. Where shelter providers did not keep
precise records, they were asked to estimate as closely as possible. In
this way an estimate of the number of sheltered homeless people was
developed. Estimating the number of homeless people not sheltered
presented greater problems. Here again, the investigators asked the
informed service providers and other concerned agencies to estimate how
many people in their jurisdictions were homeless but not in shelters on
given nights. The responses provided very wide ranges of estimates, so
the investigators devised weighting systems to be applied to the different
counties depending on their levels of economic development and orga-
nization. They also employed expert informants to estimate the propor-
tions of homeless people who may not ever come in contact with shelter
providers and thus would not even be included in the unsheltered estimate.
They developed adjustment factors based on these estimates, despite the
fact that there was little unanimity as to the size of this hidden population.
They expressed the view that their estimates probably were very con-
servative. In this way, they concluded that on an average night in 1985,
1,000 homeless people were sheltered in Maryland and that there were
an additional 1,900 unserved homeless people. Of this total population
of 2,90O, 1, 1 60 were in the city of Baltimore; the remainder were distributed
throughout the state.
The report briefly mentioned another figure: 28,O38 people "reported
sheltered during Fiscal Year 1985." The report was careful to point out
OCR for page 173
APPENDIX B 173
that this figure is not based on unduplicated data, but on reports from
shelter providers about annual volumes of service. The wide difference
between this number and the one-night estimate illustrates the hazards
of accepting service provider data without very careful consideration of
how the data were obtained or whether they represented point or period
estimates.
Another statewide indirect count was that done by the Department of
Social Services in New York State in 1984 (New York State Department
of Social Services, 19841. One thousand agencies were contacted to
ascertain whether they were shelter providers. Two hundred and fifty
shelter providers were finally identified from this list. Data from these
providers led to an estimate of 20,210 single persons and family members
as the average nightly sheltered population. In order to allow for the
numbers of homeless people outside the shelter system, they used ratios
of shelter: street populations derived from studies in Boston and Pittsburgh
to arrive at a total statewide estimate of 50,362. The authors acknowledge
that the use of these ratios, derived from estimates obtained by different
methods in very different settings, is questionable. Additional data
supplied by the shelter providers as well as by hospitals, police depart-
ments, and other informants supplemented the counts, to give more
information on the composition of the homeless population.
SINGLE-CONTACT CENSUSES
The single-contact census is a technique that has been used in cities
to make estimates of the size of their homeless populations. The census
is usually taken by teams of individuals in a clearly defined area where
preliminary studies suggest that the largest proportion of the homeless
population can be found. A screening questionnaire, or, at the very least,
instructions for selecting individuals to approach, are given to the teams
conducting the census. Under optimum conditions the census should be
conducted in a single day, preferably during a time of day when the
homeless people are most likely to be stationary, such as late at night.
However, for practical reasons, many censuses of this type are conducted
over a short period of time with some mechanism for recognizing and
eliminating duplications.
The advantages of a single-contact census are twofold: It provides for
direct contact, even if only by observation so that the possibility of
counting individuals more than once is reduced, and there is greater
assurance that the people contacted fit the study's definition of home-
lessness. In addition, demographics and other information can be obtained
that may be crucial to determining the type and level of services that
need to be provided for this population.
OCR for page 174
174 APPEN DIX B
There are also two primary disadvantages of a single-contact census.
The census provides a cross-sectional view of the population at a single
point in time, but because the homeless population appears to be in a
constant state of flux (Bachrach, 1984; Bassuk, 1984; Lamb, 1984; Fischer
and Breakey, 1986), it is out of date almost immediately after it is taken.
Moreover, it may poorly represent the true homeless population if taken
at the wrong time. If, for example, the number of homeless people on
the streets is reduced on the few days after welfare or various types of
social assistance payments become available, the number of homeless
people may be underestimated.
Another disadvantage of a single-contact census is that it is expensive
relative to indirect estimation. It is necessary to use a team of enumerators
to comb areas of the city where data are being collected. For reasons of
safety, workers are usually deployed in teams of at least two people who
are often accompanied by off-duty police officers. Staffing costs are thus
quite high.
An excellent single-contact census of the urban homeless was conducted
in Washington, D.C., by the Center for Applied Research and Urban
Policy of the University of the District of Columbia (Robinson, 1985~.
The study was carefully designed, and its techniques and assumptions
are carefully documented. The investigators counted all the residents of
the various shelters in Washington on a specific night, July 31, 1985, and
obtained counts of homeless people in hospitals and other institutions.
They supplemented this with a search of other places on the streets
where people may be found at night. The city was divided into 20 count
areas, with an enumerating team assigned to each area. The enumerators
worked in pairs; each pair included a research assistant and a person
experienced in working with the homeless. The investigators recognized
that a certain number of homeless people would fail to be counted either
because their appearance was unremarkable or because they chose
concealed locations in which to sleep. An intensive search was therefore
made in one area of the city with an augmented team that included a
police officer to judge to what extent the less intensive counts may have
failed to find homeless individuals who were hidden from view. A series
of five estimates were made, based on the direct counts and including
corrections for the two sources of error, underenumeration because
people were not identified as homeless and underenumeration because
people were actively avoiding being counted. The estimates ranged from
4,347 to 7,152, with the highest value being 64 percent larger than the
lowest value.
Other recent single-count censuses have been conducted in a number
of cities by surveying homeless people at sites that provide services,
such as shelters, soup kitchens, and social service departments (Brown
OCR for page 175
APPEN DIX B 175
et al., 1983; Chaiklin, 1983; McGerigle and Lauriat, 19831. However,
with survey sites of this sort there is an increased risk of duplication.
This risk can be minimized by including brief screening questions and by
restricting the data collection activities to a relatively short period.
Surveys at sites that provide services can also have the problem of being
dependent on agency personnel who may abandon or ignore the data
collection because it interferes with their provision of services.
Multiple-count studies expand on the single-count methodology by
conducting counts at two or more points in time. These studies are
designed so that the counts are combined to produce a single estimate.
Such studies provide additional information about changes in the popu-
lation over time, documenting seasonal and other variations.
A recent study of this type was conducted in Chicago in 1985 and 1986,
by Rossi and colleagues (19861. First, all homeless people in shelters
were counted. Then, in order to estimate the number of street people, a
survey design was developed to sample blocks in the city where homeless
people were expected to concentrate according to information obtained
from police and other informants. These blocks were then surveyed by
research workers accompanied by police officers. This process was
repeated 6 months later. Despite much effort, the yield of homeless
people on the streets that were counted by this technique was very low,
with only 22 being identified on the first occasion and 28 on the second.
Based on these institutional and street samples, estimates were derived
for the total homeless population of Chicago. The estimates, 5,907 on
the first occasion and 3,719 on the second, were widely criticized by
people familiar with homelessness in Chicago as being much too low.
Previous estimates, derived by indirect methods, ranged from 12,000 to
25,000 (Chicago Department of Human Services, 1983J. Another finding
that casts doubt on the conclusions of this study is that no children were
included in the counts of people on the streets, though families with small
children are believed to make up as much as 40 percent of Chicago's
homeless population (U.S. Conference of Mayors, 1986~. Applebaum
(1986) points out that many of the homeless people contacted on the
streets may have denied that they were homeless. It is amazing that in a
sample of blocks identified as likely places to encounter the homeless,
only 22 of 318 individuals encountered would be homeless in phase I of
the study, and only 28 of 289 would be homeless in phase II. Rossi and
associates (1986) admitted that even when the police officers who
accompanied the interviewers were not immediately introduced, subjects
were always able to identify them as police officers, and therefore, they
started the interaction on a negative note. In addition, the teams conducted
preliminary observations of the blocks before any formal screening started,
thereby tipping off a naturally suspicious population to their presence.
OCR for page 176
176 APPENDIX B
Having two counts enabled the investigators to comment on the differences
in the findings obtained in October 1985 compared with those obtained
in March 1986. In view of the methodological problems described above,
however, the validity of these conclusions must be held in question.
Another multiple-count census was done in Nashville (Wiegard, 1985),
where the homeless were counted on four separate occasions (the first
day of each season) over the course of a year. Because Nashville is a
much smaller city, the elaborate sampling frame used in the Chicago
study was not needed and the entire downtown area could be surveyed
during a single night. Demographic distributions observed at different
times were used to draw conclusions about the changing nature of the
homeless population in Nashville. The study concluded that although the
estimated numbers of homeless people varied relatively little, from 689
to 836, the ratios of homeless found in shelters compared with the
homeless found on the streets varied with the seasons. During the winter
the ratio was found to be 25:1, but in the fall the ratio was 5:1.
Such ratios have been a focus of interest in several studies, including
the study done for New York State by its Department of Social Services
described above. The HUD report used an estimate that the shelter to
street ratio was about 1:2 (Bobo, 1984~. This estimate was derived from
ratios of 100:129 estimated for Boston (Boston Emergency Shelter
Commission, 1983), 100:130 for Pittsburgh (Winograd, 1982), and 100:273
for Phoenix (Brown et al., 19831.
Freeman and Hall (1986) attempted to use a ratio of this sort based on
a survey of about 500 homeless people in New York City to make
generalizations about the national homeless population. Apart from the
obvious criticism that there is no logical basis for generalizing from New
York City to the country as a whole, the many problems with this study
included the local and unusual nature of their survey sample and their
failure to take into account the cyclical patterns of homelessness. In
attempting to generalize from their ratios to the national level, they based
their estimates on the flawed HUD data and failed to take into account
the variability of street:shelter ratios described above for various cities.
Their conclusions, therefore, must be interpreted with considerable
skepticism.
CAPTURE-RECAPTURE METHODS
Capture-recapture methods go beyond multiple-count methods by
matching data on individuals observed at two or more points in time.
They thus permit certain conclusions about the movement of individ-
uals in and out of the population, as well as statistics about the popu-
lation from which the sample was drawn. Capture-recapture techniques
OCR for page 177
APPENDIX B 177
involve matching observations of individuals made at each of two or
more data collection periods. In wildlife populations, for which this
technique was developed, captured animals were tagged for ready iden-
tification on recapture. Matching of homeless individuals is achieved by
using a combination of name, Social Security number, birth date, sex,
race, and other unique identifiers. In matching subjects from the first
observation to the second, the resulting data can be tabulated as shown
in Table B-1.
The values in Table B- 1 represent counts of people observed at different
times: N. represents the count of those obtained during the first data
collection period, N2 represents the count of those obtained during the
second data collection period, and M represents the number matched,
that is, the number observed both times. The only number missing from
Table B-l that cannot be easily calculated by subtraction is the number
of people in the population not observed in either the first or second
period.
Two estimates of the number of homeless people in an area are possible
from Table B-1. The first assumes that the census was complete and that
the missing cell (not observed in either period) actually should have an
entry of one. This estimate of the total number of homeless would be
calculated as N. + N2 - M (Equation B-11. This estimate would then
be merely a lower bound to the actual number of homeless, since in
reality no census is complete and there are hidden homeless who remain
uncounted no matter how strenuous an effort is made.
A second estimate can be calculated from Table B-1 that does not
assume that there are no hidden homeless, and this is the estimate by
the capture-recapture method. This assumes that each data collection is
imperfect, that there is some probability at each data collection that
individuals will be missed, and that consequently there is some (unknown)
probability that individuals will be missed both times. The estimate of
the total number of homeless from a capture-recapture study can be
calculated from the formula (N. x N~/M (Equation B-21. Capture-
recapture estimates have been used for biometric applications for several
TABLE B-1 Observation of the Homeless in
Two Periods of Time
Second Period of Time
First Period of
Time Matched Not Matched Total
Matched
Not matched
Total count No
A]
N.
OCR for page 178
178 APPENDIX B
hundred years, chiefly in making estimates of the size of wildlife popu-
lations, and the basic estimator (Equation B-2) has been rederived in
several different contexts. One of the earliest use of capture-recapture
techniques for human populations was for the evaluation of the complete-
ness of birth and death records (Chandrasekar and Deming, 19491. The
most common application currently is for the evaluation of population
and agriculture censuses (Cowan et al., 1986~. Also called dual-system
estimation in this context, evaluations of censuses by capture-recapture
studies have been conducted in the United States, Paraguay, Bangladesh,
India, and other countries. The evaluation of the census and use of the
capture-recapture method in Somalia is of particular interest, since 60
percent of that country's population is nomadic and, in this respect, is
similar to a homeless population. Additional information on a population
can be obtained from making more than two observations. In recent
years, maximum likelihood techniques have been used to derive estimates
for use in studies involving several sampling periods (Bishop et al., 1976~.
There are two studies of homeless populations that make use of capture-
recapture techniques. The first was a study of the number of homeless
men in Sydney, Australia (Darcy and Jones, 19751. In that study of
homeless men, three 1-day censuses were conducted at 25 locations
including shelters, hospitals, clinics, and a jail, on June 30, 1971; October
13, 1971; and March 8, 1972. Using Equation B-2, three estimates of the
number of homeless men were obtained by comparing the three sets of
data, two at a time, with the following results: June to October, 3,025;
June to March, 4,119; and October to March, 3,322. The authors used a
related technique that makes use of information from all three data sets
to yield an overall estimate of the number of homeless men in Sydney
(3,200~. They also estimated the average "birth" and "death" rates for
men entering and leaving the homeless population to be 21 and 5 percent,
respectively, indicating that the homeless population was increasing over
the period of the study.
It should be noted from the estimates presented above that the longer
the interval between counts, the higher the estimate. The authors noted
that the intervals between censuses were sufficiently long to allow entry
and exit from the homeless population, through moving in and out of
Sydney, deaths, and so on, so that the numbers of matches were reduced.
If shorter time intervals had been used, it might be supposed that the
estimates would have been lower.
The other study that used the capture-recapture method was conducted
in Baltimore in 1985 and 1986 (Cowan et al., 19861. Four pairs of dates
were chosen in August and November 1985 and in February and May
1986 to reflect the four seasons; each pair was used for a capture-recapture
OCR for page 179
APPENDIX B 179
estimate. Data were entered on separate computer files for the eight
counts, and a computer program was written to match individuals between
counts. Each of the four pairs of counts permitted a capture-recapture
estimate of the total number of potential shelter users in the city on an
average night in that month. The results indicated that the number of
people in the shelter-using population did not vary significantly across
the seasons, ranging from 874 to 1,022. The counts also showed that on
all eight nights the shelter beds in the city were filled close to capacity.
From the computer lists it was possible to create a master file of individuals
observed at any of the eight sampling periods, including demographic
information and a record of sample in which they were included. The
master file included 2,102 people, of whom 66 percent were men and 34
percent were women. Analysis of the patterns of recurrence of individuals
in successive samples provided information on the dynamics of people
entering and leaving the homeless population.
In order to make an estimate of the proportion of homeless people
who do not use the shelter system, a street survey was conducted in
December 1986. People were questioned very briefly in places where
homeless people congregate, but do not sleep, such as soup kitchens,
day shelters, or on the streets. The brief questionnaire asked whether
they had a place to live, and if not, did they use the shelter system, and
if so, when was the most recent occasion. This information was then
used to supplement the capture-recapture estimates. It was found that
about three-quarters of those questioned were potential shelter users.
Taking this into account, the capture-recapture estimates from this study
provided estimates that were very compatible with those obtained by the
indirect survey method in the Health and Welfare Council of Central
Maryland (1986) study described above, in which the total number
estimated for Baltimore was 1,160 and the sex ratio was 64 percent male
to 36 percent female.
The most important difference between the capture-recapture technique
and the two methods described earlier is that the capture-recapture
technique is the only one that involves a statistical model to estimate the
size of the unseen portion of the population. Single- or multiple-count
censuses require some correction or expansion on the counts obtained,
to allow for the hidden homeless who are not included in shelter counts,
or in the case of the single-contact census, who may not even be picked
up in a well-done street census. The correction factors used in most
studies did not seem to be calculated under any rigorous statistical
procedure but, rather, rejected the ratio the researchers wanted to obtain.
A statistical model involves a number of assumptions about factors
that affect or, perhaps more important, that do not affect the data
OCR for page 180
180 APPENDIX B
collection process. The most important assumptions in the capture-
recapture method are listed below:
1. Clear definitions: Homeless people can be accurately identified.
2. Homogeneous observation probabilities: Each person has the same
chance of being observed in a specific period.
3. Stability: The size and nature of the population does not change
during the observation period.
4. Stationarity: The population does not move in or out of the study
area during the observation period.
5. Independent captures: For the periods, the order interaction term
(however defined) is zero; that is, even though a homeless person was
observed at one period, it does not affect the probability that the person
will be observed on subsequent occasions.
6. Data correctness: The information collected is accurate.
7. Complete response: Individuals or informants provide information
that is complete enough to permit matching.
8. Matching correctness: Data records for the same individuals can be
linked between observation periods.
9. Single observations: Individuals are observed only once at each
data collection.
10. Known externalities: Factors that affect the data collection are
known and can be accounted for, such as weather conditions and receipt
of welfare checks.
Violations of these assumptions invalidate the model, causing the
results to be biased (Cowan, 1982, 19841. More complex models allow
for all exigencies, but more complex models require more data and may
be impractical.
DISCUSSION
Although the existence of a sizable homeless population is beyond
doubt and there is a consensus among knowledgeable people that the
extent of the problem has been increasing in recent years, the ever-
changing and fluid nature of the homeless population presents great
methodological challenges in obtaining an accurate measure of its size.
A review of the methods for estimating the number of homeless people
indicates that great caution should be exercised in interpreting any of the
available data. Each of the methods that has been used has inherent
biases. There is no national estimate that is based on a sound methodology
arid that is agreed to be accurate. Estimates prepared for individual
communities or cities may be more accurate, but here also, careful
scrutiny of methodology is required to assess such data adequately.
OCR for page 181
APPENDIX B 181
In order to advance research in this area, developmental work is needed
in three specific areas:
Definitions must be developed concerning who is considered home-
less. Agreement on a definition is vital if valid comparisons between
studies are to be made. Subgroups, such as homeless families, should
also be defined.
2. There is a need for more comparative research to determine better
methodologies for studying difficult to find or difficult to enumerate
populations. An example would be research in the use of network or
multiplicity sampling for making estimates of the size of the homeless
population in cities.
3. There is a need for more comprehensive capture-recapture models.
Such models would permit data from several sources to be used and
adjustments for missing data to be incorporated into the model.
Future research must pay very careful attention to the biases introduced
by the different enumeration methods. Research teams must take advan-
tage of the knowledge of people who are familiar with the homeless
population in designing data collection techniques and in defining and
identifying homeless people. Even with careful attention to methodological
issues, it may not be practical or possible to develop a valid national
estimate of the total number of homeless people. If, however, studies
are carried out in cities and communities across the country using clear
definitions and clearly defined methods, a composite picture may be built
that will ultimately be more informative.
REFERENCES
Applebaum, R. P. 1986. Counting the homeless. Paper prepared for the George Washington
University Conference on Homelessness.
Bachrach, L. L. 1984. The homeless mentally ill and mental health services: An analytic
review of the literature. In The Homeless Mentally Ill, H. R. Lamb, ed. Washington,
D.C.: American Psychiatric Association.
Baltimore City Council. 1983. Report of the Baltimore City Task Force for the Homeless.
Baltimore: Baltimore City Council.
Bassuk, E. L. 1984. The homeless problem. Scientific American 251(1):40-45.
Bishop, Y. M. M., S. E. Feinberg, and P. W. Holland. 1976. Discrete Multivariate Analysis.
Cambridge, Mass.: MIT Press.
Bobo, B. F. 1984. A Report to the Secretary on the Homeless and Emergency Shelters.
Washington, D.C.: U.S. Department of Housing and Urban Development.
Boston Emergency Shelter Commission. 1983. The October Project: Seeing the Obvious
Problem. Boston: Boston Emergency Shelter Commission.
Brown, C., S. McFarlane, R. Paredes, and L. Stark. 1983. The Homeless of Phoenix: Who
Are They and What Should Be Done? Phoenix, Ariz.: Phoenix South Community
Mental Health Center.
Chaiklin, H. 1983. The service needs of soup kitchen users. Baltimore: School of Social
Work and Community Planning, University of Maryland. (Unpublished.)
OCR for page 182
182 APPENDIX B
Chandrasekar, C., and W. E. Deming. 1949. On a method of estimating birth and death
rates and the extent of registration. Journal of the American Statistical Association
44: 101-115.
Chicago Department of Human Services. 1983. Homelessness in Chicago. Chicago: Chicago
Department of Human Services.
Cowan, C. D. 1982. Modifications to capture-recapture estimation in the presence of errors
in the data. Paper presented at the meetings of the American Statistical Association,
Biometrics Section, Cincinnati.
Cowan, C. D. 1984. The Effects of Misclassification on Estimates from the Capture-
Recapture Studies. Unpublished Ph.D. dissertation. The George Washington Univer-
sity, Washington, D.C..
Cowan, C. D., W. R. Breakey, and P. J. Fischer. 1986. The methodology of counting the
homeless. In Proceedings of the American Statistical Association, Survey Research
Methods Section. Alexandria, Va.: American Statistical Association.
Cowan, C. D., R. J. Magnani, P. P. Biemer, and A. G. Turner. 1985. Evaluating Censuses
of Population and Housing. Washington, D.C.: Bureau of the Census.
Darcy, L., and D. L. Jones. 1975. The size of the homeless men population of Sydney.
Australian Journal of Social Issues 10:208-215.
Emergency Food and Shelter National Board. 1983. Program Description. A board
established by Congress and the United Way. Alexandria, Va.: United Way of America.
Fischer, P. J., and W. R. Breakey. 1986. Homelessness and mental health: An overview.
International Journal of Mental Health 14(4):6-41.
Freeman, R. B., and B. Hall. 1986. Permanent Homelessness in America: Working paper
no. 2013. Cambridge, Mass.: National Bureau of Economic Analysis.
Health and Welfare Council of Central Maryland. 1983. A Report to the Greater Baltimore
Shelter Network on Homelessness in Central Maryland. Baltimore: Health and Welfare
Council of Central Maryland.
Health and Welfare Council of Central Maryland. 1986. Where Do You Go from Nowhere?
Homelessness in Maryland. Baltimore: Maryland Department of Human Resources.
Hombs, M. E., and M. Snyder. 1982. Homelessness in America: A Forced March to
Nowhere. Washington, D.C.: Community for Creative Nonviolence.
Lamb, H. R., ed. 1984. The Homeless Mentally Ill. Washington, D.C.: The American
Psychiatric Association.
McGerigle, P., and A. S. Lauriat. 1983. More Than Shelter: A Community Response to
Homelessness. Boston: United Community Planning Corporation.
New York State Department of Social Services. 1984. Homelessness in New York State:
A Report to the Governor and the Legislature. New York: New York State Department
of Social Services.
Robinson, F. G. 1985. Homeless People in the Nation's Capital. Washington, D.C.: Center
for Applied Research and Urban Policy, University of the District of Columbia.
Rossi, P. H., G. A. Fisher, and G. Willis. 1986. The Condition of the Homeless in Chicago.
A report prepared by the Social and Demographic Research Institute, University of
Massachusetts at Amherst, and the National Opinion Research Center, University of
Chicago.
U.S. Conference of Mayors. 1986. The Continued Growth of Hunger, Homelessness and
Poverty in America's Cities: 1986. A 25-City Survey. Washington, D.C.: U.S.
Conference of Mayors.
Wiegard, R. B. 1985. Counting the homeless. American Demographics 7(12):34-37.
Winograd, K. 1982. Street People and Other Homeless: A Pittsburgh Study. Pittsburgh:
The Emergency Shelter Task Force.
Representative terms from entire chapter:
homeless population
