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survey. Service companies that provided this information included National Water <strong>and</strong> Power,<br />

Viterra, <strong>and</strong> Archstone. The web information was provided by a Texas utility registry<br />

(http://www.tceq.state.tx.us/index.html) <strong>and</strong> was only applicable to San Antonio <strong>and</strong> Austin.<br />

The number of properties identified through each source can be seen in Table 3.3. All in all,<br />

about 15% of all the surveys sent were obtained from sources other than the postcard survey.<br />

Table 3.3 Manager survey properties identified through service companies <strong>and</strong> a Texas<br />

web site registry<br />

Properties Identified<br />

Through:<br />

Total<br />

Service Web<br />

City<br />

Companies* Registry †<br />

Austin 15 142 157<br />

Denver 23 - 23<br />

Oakl<strong>and</strong> 17 - 17<br />

Hills 8 - 8<br />

Indianapolis 5 - 5<br />

Irvine 18 - 18<br />

Las Vegas 9 - 9<br />

Phoenix 35 - 35<br />

Portl<strong>and</strong> 11 - 11<br />

San Antonio 4 79 83<br />

San Diego 35 - 35<br />

Seattle 9 - 9<br />

Tucson 31 - 31<br />

Total 220 221 441<br />

* Service companies include National Water <strong>and</strong> Power, Archstone, <strong>and</strong> Viterra<br />

†<br />

Web properties are only for Austin <strong>and</strong> San Antonio<br />

Since a lower percentage of impact properties were identified than originally anticipated,<br />

a saturation sampling technique was chosen for the manager survey so that every identified<br />

impact property received a manager survey. Within each city, impact properties were placed into<br />

bins according to number of units. The bin ranges for each city were determined by ordering all<br />

units in descending order <strong>and</strong> dividing them equally into thirds. Then, a stratified r<strong>and</strong>om<br />

sample of in-rent properties was drawn from corresponding bins. The goal was that for<br />

approximately every 1.2 impact surveys sent, 2 in-rent surveys would be sent. For example, if a<br />

city had 24 impact properties identified in its lowest bin (10 – 100 units), then about 40<br />

properties would be picked from the in-rents that fell within the same bin range. If there were<br />

41

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