{"id":97329,"date":"2002-06-23T00:00:00","date_gmt":"2002-06-23T05:00:00","guid":{"rendered":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/2002\/06\/23\/methodology-149-2\/"},"modified":"2024-04-14T04:14:28","modified_gmt":"2024-04-14T09:14:28","slug":"methodology-149-2","status":"publish","type":"post","link":"https:\/\/alpha.pewresearch.org\/pewresearch-org\/internet\/2002\/06\/23\/methodology-149-2\/","title":{"rendered":"Methodology"},"content":{"rendered":"<p class=\"wp-block-paragraph\">This report is based on the findings of a survey of Americans about their use of the Internet.\u00a0 The results are based on data from telephone interviews conducted by Princeton Survey Research Associates between January 29 and February 20, 2002, among a sample of 507 Internet users, 18 and older, who have broadband Internet access.\u00a0 For results based on the total sample, one can say with 95% confidence that the error attributable to sampling and other random effects is plus or minus 4 percentage points.\u00a0 In addition to sampling error, question wording and practical difficulties in conducting telephone surveys may introduce some error or bias into the findings of opinion polls.<\/p>\n\n<p class=\"wp-block-paragraph\">Interviews for this survey were completed from a pre-screened sample of Internet users who in past surveys identified themselves as having broadband Internet access.\u00a0 Once the household was reached, interviewers asked to speak with the individual who had recently completed a telephone survey.\u00a0 Once the targeted person was on the phone, they were asked a few screening questions to make sure that they still had high speed Internet access at home.<\/p>\n\n<p class=\"wp-block-paragraph\">At least 10 attempts were made to complete an interview at every household in the sample.\u00a0 The calls were staggered over times of day and days of the week to maximize the chances of making contact with a potential respondent.\u00a0 Interview refusals were re-contacted at least once in order to try again to complete an interview.<\/p>\n\n<h3 data-is-section=\"true\" data-wp-context=\"{&quot;id&quot;:&quot;appendix-a-internet-activities&quot;}\" data-wp-interactive=\"{&quot;namespace&quot;:&quot;prc-block\\\/table-of-contents&quot;}\" id=\"appendix-a-internet-activities\" class=\"wp-block-heading\">Appendix A: Internet Activities<\/h3>\n\n<p class=\"wp-block-paragraph\"><figure><img loading=\"lazy\" decoding=\"async\" width=\"463\" height=\"745\" alt=\"Appendix A: Internet activities\" src=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/internet\/wp-content\/uploads\/sites\/9\/media\/33C468233D484323957E7CE4416A93A0.jpg\" class=\"aligncenter\"><\/figure>\n<\/p>\n\n<h3 data-is-section=\"true\" data-wp-context=\"{&quot;id&quot;:&quot;appendix-b&quot;}\" data-wp-interactive=\"{&quot;namespace&quot;:&quot;prc-block\\\/table-of-contents&quot;}\" id=\"appendix-b\" class=\"wp-block-heading\">Appendix B<\/h3>\n\n<p class=\"wp-block-paragraph\">In this report\u2019s section \u201cChanges in behavior: Broadband access is a decisive factor\u201d, we discuss some of the causal factors underlying our finding that home broadband access makes the key difference for the surfing habits of high-speed users.\u00a0 This appendix elaborates on the statistical techniques employed that are the basis for that finding.\u00a0 We used regression analysis, a statistical technique that isolates the independent effects of various factors (e.g., demographics or a home broadband connection) to examine what drives the intensity of home Internet use.<\/p>\n\n<p class=\"wp-block-paragraph\">The analysis assesses the intensity of users\u2019 online behavior by looking at three variables: <\/p>\n\n<ul class=\"wp-block-list\">\n<li>the likelihood that someone answers \u201cyes\u201d to the question \u201cDid you go online yesterday?\u201d <\/li>\n<li>the amount of time spent online during a typical day<\/li>\n<li>how many activities he performs on a typical day online<\/li>\n<\/ul>\n\n<p class=\"wp-block-paragraph\">The table below summarizes the results from the regression analysis, which examined the traits or outside forces that might influence people\u2019s Internet use. The horizontal rows contain the independent variables\u2014the factors we seek to explain\u2014and the vertical rows contain the dependent variables\u2014the things that may explain the observed outcomes (e.g., going online on a daily basis).\u00a0 The explanatory variables are the things that might conceivably affect the intensity of someone\u2019s Internet use: a home broadband connection, number of years online, age, income, education gender, and race.\u00a0 <\/p>\n\n<p class=\"wp-block-paragraph\"><figure><img loading=\"lazy\" decoding=\"async\" width=\"529\" height=\"304\" alt=\"Appendix B: Determinants of intensity\" src=\"https:\/\/alpha.pewresearch.org\/pewresearch-org\/internet\/wp-content\/uploads\/sites\/9\/media\/A96D7B8844364334B2A7E6627D611423.jpg\" class=\"aligncenter\"><\/figure>\n<\/p>\n\n<p class=\"wp-block-paragraph\">For \u201cgoing online yesterday\u201d, the dependent variable is binary (i.e., coded as 1 for those who answer \u201cyes\u201d) and logistic regression is used in the analysis.\u00a0 For the amount of time spent online on a given day, we asked users to estimate the amount of time they spend online.\u00a0 Those who say they spend more than 2 hours online per day are coded as 1, and those who spend less than 2 hours are coded as 0 for the purposes of a logistic regression.\u00a0 The number of activities done on a typical day is a continuous variable, with ordinary least squares used in the regression analysis.\u00a0 <\/p>\n\n<p class=\"wp-block-paragraph\">The results show that having a home broadband connection, number of years online,[3.numoffset=&#8221;3&#8243; The variable for number of years online is a \u201cdummy\u201d variable that takes on the value 1 if a user has had Internet access for 6 or more years. About 35% of Internet users have been online for 6 or more years.] and gender are the only factors that explain intensity of Internet use consistently in all three specifications.\u00a0 Although numbers are not reported, having a home broadband is the <i>largest single factor<\/i> that explains going online daily, spending two or more hours online daily, or doing a greater number of Internet activities.\u00a0 For the logistic regressions, exponentiated coefficients allow us to compare the relative magnitudes of the predictive power of significant variables.\u00a0 For the ordinary least squares regression, the fact that having a broadband connection, number of years online, and gender are all \u201cdummy\u201d variables permits comparison of the relative magnitudes of variables\u2019 explanatory power.<\/p>\n\n<p class=\"wp-block-paragraph\">In short, having a home broadband connection and having been online for a long time both increase your chances of using the Internet intensively.\u00a0 But the home broadband connection increases your chances more.\u00a0<\/p>","protected":false},"excerpt":{"rendered":"<p>This report is based on the findings of a survey of Americans about their use of the Internet.\u00a0 The results are based on data from telephone interviews conducted by Princeton Survey Research Associates between January 29 and February 20, 2002, among a sample of 507 Internet users, 18 and older, who have broadband Internet access.\u00a0 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