Community Life and Housing in Rural Nebraska: 2005 Nebraska Rural Poll Results

Many rural communities are experiencing population decline. However, rural residents have continued to show a strong attachment to their communities. How do rural Nebraskans feel about their community? Are they satisfied with the services provided? Do they own their home? What is the condition of their home? This report details 2,851 responses to the 2005 Nebraska Rural Poll, the tenth annual effort to understand rural Nebraskans’ perceptions. Respondents were asked a series of questions about their community and housing. Trends for some of these questions are examined by comparing data from the nine previous polls to this year’s results. For all questions, comparisons are made among different respondent subgroups, that is, comparisons by age, occupation, region, etc. Based on these analyses, some key findings emerged: Rural Nebraskans’ views of the change in their community are similar to those expressed last year. This year, 28 percent believe their community has changed for the better, compared to 26 percent last year. And, in 2005, only 20 percent think their community has changed for the worse, compared to 22 percent last year. The proportion of expected movers who plan to leave the state decreased this year. Last year, 56 percent of the persons planning to move from their community expected to leave the state. That proportion decreased to 47 percent this year. Rural Nebraskans living in or near the largest communities are more likely than persons living in or near the smaller communities to say their community has changed for the better. Thirty-nine percent of persons living in or near communities with populations of 10,000 or more believe their community has changed for the better during the past year, but only 15 percent of persons living in or near communities with less than 500 people share this opinion. The community services and amenities that rural Nebraskans are most dissatisfied with include: entertainment, retail shopping and restaurants. At least one-third of rural Nebraskans express dissatisfaction with these three services. They are most satisfied with parks and recreation, library services, basic medical care services, highways and bridges, and education (K - 12). At least one-half of rural Nebraskans are satisfied with the following items in their community: appearance of residential areas (66%), crime control (61%), maintenance of sidewalks and public areas (57%) and noise (54%). Rural Nebraskans generally have positive views about their community. Sixty percent agree that their community is an ideal place to live and 52 percent say their community has good business leaders. Rural Nebraskans have mixed opinions about the future of their community. Fortyfour percent agree that their community’s future looks bright, but 42 percent disagree with this statement. Fourteen percent have no opinion. Rural Nebraskans living in or near the larger communities are more likely than residents of the smaller communities to think their community’s future looks bright. Fifty-nine percent of persons living in or near communities with populations of 10,000 or more agree with this statement, compared to only 25 percent of residents living in or near communities with less than 500 people. Further, 61 percent of the residents of the smallest communities disagree with this statement, compared to only 28 percent of the residents of the largest communities. Over three-quarters of rural Nebraskans disagree that younger residents of their community tend to stay there after completing high school. Seventy-six percent disagree with this statement, 16 percent have no opinion and eight percent agree that younger residents stay after completing high school. When comparing responses by age, younger persons are more likely than older persons to agree that younger residents stay in their community after high school. Sixteen percent of persons age 19 to 29 agree with this statement, compared to only six percent of persons age 50 to 64. Younger persons are more likely than older persons to be planning to move from their community next year. Fifteen percent of persons between the ages of 19 and 29 are planning to move next year, compared to only two percent of persons age 65 and older. An additional 17 percent of the younger respondents indicate they are uncertain if they plan to move. Most rural Nebraskans own their home. Eighty-four percent of rural Nebraskans own their home. Older persons are more likely than younger persons to own their home. Eighty-eight percent of persons over the age of 50 own their home, compared to only 52 percent of persons age 19 to 29. Housing in rural Nebraska has an average age of 50 years. Twenty-four percent of residences were built before 1930. Another 24 percent were built between 1930 and 1959. Twenty-nine percent were built between 1960 and 1979 and the remaining 24 percent were built in 1980 or later. The housing stock in smaller communities is older than the housing located in larger communities. Over one-third (35%) of the residences in communities with less than 1,000 people were built before 1930. Only 12 percent of the homes in communities with populations of 10,000 or more were built in this time period. Most rural Nebraskans appear satisfied with their home. Only 24 percent say the current size of their home does not meet their needs. The same proportion (24%) say their home is in need of major repairs. Thirty-eight percent agree that their home needs a lot of routine maintenance, but 87 percent like the location (neighborhood) of their home. One-third of rural Nebraskans living in or near the smallest communities say their home is in need of major repairs. Only 19 percent of persons living in or near communities with populations of 5,000 or more are facing this problem. Home ownership is very important to most rural Nebraskans. Eighty-two percent believe it is very important to own their home. An additional 12 percent say it is somewhat important and six percent say it is not at all important. However, persons who do not currently own their home do not feel it is important for them to do so. Only 32 percent of renters say it is very important to own their home, compared to 91 percent of home owners. And, 35 percent of renters say it is not at all important to own their home.

Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Evaluating Measurement Invariance with Censored Ordinal Data: A Monte Carlo Comparison of Alternative Model Estimators and Scales of Measurement

Evaluations of measurement invariance provide essential construct validity evidence. However, the quality of such evidence is partly dependent upon the validity of the resulting statistical conclusions. The presence of Type I or Type II errors can render measurement invariance conclusions meaningless. The purpose of this study was to determine the effects of categorization and censoring on the behavior of the chi-square/likelihood ratio test statistic and two alternative fit indices (CFI and RMSEA) under the context of evaluating measurement invariance. Monte Carlo simulation was used to examine Type I error and power rates for the (a) overall test statistic/fit indices, and (b) change in test statistic/fit indices. Data were generated according to a multiple-group single-factor CFA model across 40 conditions that varied by sample size, strength of item factor loadings, and categorization thresholds. Seven different combinations of model estimators (ML, Yuan-Bentler scaled ML, and WLSMV) and specified measurement scales (continuous, censored, and categorical) were used to analyze each of the simulation conditions. As hypothesized, non-normality increased Type I error rates for the continuous scale of measurement and did not affect error rates for the categorical scale of measurement. Maximum likelihood estimation combined with a categorical scale of measurement resulted in more correct statistical conclusions than the other analysis combinations. For the continuous and censored scales of measurement, the Yuan-Bentler scaled ML resulted in more correct conclusions than normal-theory ML. The censored measurement scale did not offer any advantages over the continuous measurement scale. Comparing across fit statistics and indices, the chi-square-based test statistics were preferred over the alternative fit indices, and ΔRMSEA was preferred over ΔCFI. Results from this study should be used to inform the modeling decisions of applied researchers. However, no single analysis combination can be recommended for all situations. Therefore, it is essential that researchers consider the context and purpose of their analyses.